Understanding Online Hate Toward Sexual and Gender Minorities: A Systematic Review

Abstract

Online hate speech (OHS) refers to discriminatory or offensive content shared via digital platforms that targets social groups. Synthesizing evidence on OHS directed at sexual and gender minorities (SGMs) is crucial, given the disproportionate online discrimination experienced by SGM people and its implications for well-being and social norms. This PRISMA-based systematic review synthesized quantitative studies in which the target of OHS content was SGM people, regardless of whether participants were SGM or non-SGM. We addressed four questions: (a) OHS definitions and operationalizations; (b) prevalence and risk factors of OHS; (c) psychological, behavioral, and social outcomes of exposure; and (d) behavioral responses to OHS exposure. Searches of 5 databases identified 13 studies. Definitions varied but generally captured identity-based targeting and hostile content in public or semi-public digital spaces. Prevalence varied by sampling frame: SGM-only studies reported high exposure (often > 85%), whereas general-population studies reported lower prevalence but higher exposure among SGM respondents. Risk factors were identity visibility/engagement, online behaviors, and lower digital media literacy; perpetration evidence was scarce. Exposure was associated with poorer SGM well-being (e.g., depression/anxiety, substance use, concealment, identity threat) and, experimentally, with lower perceived social cohesion and mixed effects on social attitudes. Witnesses generally condemned anti-SGM OHS; tolerance was higher among users with more negative pre-existing attitudes. Perceiving OHS as uncivil or harmful predicted stronger intervention intentions, while counter-speech effects were modest, reducing identity threat mainly under milder OHS. Findings highlight the need for harmonized measures, longitudinal/intersectional designs, and interventions pairing platform moderation with bystander-focused prevention efforts.

Keywords

online hate speech LGBT cyberhate sexual and gender minorities minority stress bystander responses.

Introduction

Over the past two decades, the spread of digital technologies and the rise of social media platforms have brought several new forms of online violence to the forefront as major concerns in the virtual public sphere. This phenomenon is broadly categorized as cyberaggression, an umbrella term encompassing Online Hate Speech (OHS), harassment, stalking, and cyberbullying. These hostile behaviors significantly impact the well-being and social behavior of both targeted individuals and society at large (Bilewicz & Soral, 2020; Cervone et al., 2021). Platforms such as Instagram, TikTok, X (formerly Twitter), and YouTube, alongside interactive spaces such as online forums and website comment sections, have become arenas for both exchange and confrontation, where hostile and offensive communication can proliferate at an alarming rate and with high visibility. The potential for real-time interaction with a vast audience has created fertile ground for the dissemination of hateful content. This is further facilitated by anonymity, which allows perpetrators to act without immediate social and legal consequences (Citron, 2014; Cohen-Almagor, 2015), and by perceived social distance, which diminishes awareness of the repercussions of one’s actions (Brown, 2018). As a result, cyber violence and hate have transcended national borders, becoming a global concern affecting communities worldwide.

A prominent form of cyberaggression is OHS (Bedrosova et al., 2022; Hawdon et al., 2017; Tennakoon et al., 2021). While hate speech was initially a legal term for offline contexts, it has evolved to encompass social, cultural, political, and economic spheres across online platforms, with diverse interpretations (Brown, 2017). This broad application makes it challenging to establish consensus on the essential elements of hate speech, complicating efforts to develop a precise construct for empirical research. However, existing research generally agrees that hate speech involves expressing hatred or degrading attitudes toward a specific group (Hawdon et al., 2017). In essence, hate speech devalues people based on their membership in social groups defined by characteristics such as ethnicity, religion, nationality, gender, and sexual orientation (Hawdon et al., 2017; Keipi et al., 2017; Paasch-Colberg et al., 2021). This focus on group hostility distinguishes OHS from cyberbullying, which typically involves repeated aggression directed at a specific individual over time (Bedrosova et al., 2022; Fulantelli et al., 2022; Tokunaga, 2010). Exposure to OHS is particularly harmful because it targets social identity and group affiliations, potentially undermining self-esteem and self-worth (Van Houtven et al., 2024). By reinforcing group distinctions while devaluing targeted groups, OHS exposure can erode the self-esteem of individuals within these groups (Boeckmann & Liew, 2002) and lead to severe psychological distress, including anxiety, depression, and sleep disturbances (Delgado & Stefancic, 2019). Targets often experience increased feelings of personal responsibility for the attacks and a diminished sense of safety in their offline lives (Dreißigacker et al., 2024; Saha et al., 2019).

The impact of OHS is particularly relevant for sexual and gender minorities (SGMs), who are among the groups most frequently targeted (Hawdon et al., 2017). Minority Stress Theory (Meyer, 2003) offers a useful framework for understanding why OHS may be especially harmful for SGM people. The theory posits that stigma related to minoritized identities produces additional stress exposure that is socially generated, chronic, and additive to general life stressors. Overall, these minority stressors constitute an excess, stigma-related stress load that contributes to greater risk for negative health outcomes among SGM people compared to non-SGM people (Thoma et al., 2019; Roberts et al., 2021; Wilson & Cariola, 2020). At the same time, individual and contextual resources such as coping strategies, social support, and community connectedness can buffer the impact of minority stress. Minority Stress Theory further distinguishes between distal and proximal stressors. Distal stressors are external and objective, arising from social conditions such as discrimination, rejection, and prejudice. Proximal stressors are internal and subjective, reflecting how people perceive and navigate stigma, for example, through internalized negative beliefs about one’s identity, expectations of rejection, and efforts to conceal one’s identity.

Although these stressors have typically been examined in offline contexts of prejudice and discrimination, they have become increasingly prevalent in online environments (McConnell et al., 2017). In fact, the proliferation of social media has coincided with a rise in OHS targeting SGM communities, including homophobic and transphobic comments (Keighley, 2022). This trend aligns with the developmental collision hypothesis (Bishop et al., 2024), which suggests that increased public awareness of SGM issues over the past several decades has contributed to adolescents forming minoritized sexual identities at younger ages. While these shifting developmental contexts can be beneficial, facilitating earlier self-identification and disclosure among SGM youth, they are also associated with increased exposure to SGM-related victimization, which, in turn, correlates with higher levels of depressive symptoms (Bishop et al., 2024). Thus, OHS may operate as a distal stressor through overt hostility and digital microaggressions, while also intensifying proximal stressors. Emerging evidence suggests that exposure to OHS is associated with perceived insecurity (Dreißigacker et al., 2024) and with viewing online spaces as unsafe for SGM users (Keighley, 2022). This is particularly important because online spaces often serve as contexts where SGM youth explore, affirm, and express their identities. In this context, OHS can disrupt this process, leading to feelings of exclusion, fear, and diminished self-worth (Patchin & Hinduja, 2010). Overall, in line with Minority Stress mechanisms, SGM youth may be disproportionately vulnerable to the psychological harm of OHS compared to non-SGM youth (Keighley, 2022; McInroy et al., 2024).

Existing reviews on OHS have offered broad syntheses of the phenomenon, generally treating it as homogeneous and only rarely focusing on SGM people. Consequently, they tend to overlook both the specific ways in which OHS targets SGM people and the possibility that such hostility may be qualitatively distinct from other forms of OHS. At the same time, definitions and measurement strategies for OHS targeting SGM people remain highly heterogeneous, limiting comparability across studies and highlighting the need for greater conceptual clarity and SGM-sensitive frameworks. Given the prevalence and significant social impact of OHS, there is a critical need for research to systematically consolidate existing findings on OHS targeting SGM people.

This systematic review aims to address this need by synthesizing quantitative studies that examine OHS targeting SGM people. By consolidating current evidence on prevalence, psychological and social consequences, associated factors, and responses, the review contributes to the advancement of scholarly understanding and informs the development of evidence-based policies and interventions to mitigate the impact of online hate on SGM people. Importantly, the studies included are not restricted to SGM participants. They also include non-SGM participants, given the central role of bystanders (i.e., those who witness hateful behaviors online), whose reactions can influence the diffusion and normalization of hateful content and are themselves associated with measurable psychological and social outcomes.

Research Questions

The research literature on OHS targeting SGM people has been synthesized to answer the following research questions (RQs):

RQ1: What are the key characteristics of studies on OHS targeting SGM groups and how OHS has been defined and operationalized within existing research?

RQ2: What is the prevalence of OHS targeting SGM groups, and what factors are associated with its occurrence?

RQ3: What psychological, behavioral, and social outcomes are associated with exposure to OHS among both SGM groups and non-SGM groups?

RQ4: How do people respond or react when they witness OHS?

Method

Search Method (Design and Strategy)

This systematic review followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines (Page et al., 2021) to ensure transparency and reproducibility. We conducted a literature search across PsycINFO, Web of Science, Scopus, LGBTQ+ Source, and ERIC to ensure comprehensive interdisciplinary coverage (psychology, education, and social sciences, including scholarship focused on SGM issues). Search covered records from database inception to May 2024 and were updated in October 2024. We restricted the search to peer-reviewed journal articles written in English. We aimed to identify empirical quantitative research articles assessing OHS targeting SGM populations. We included studies in which the content target of OHS was SGM people, regardless of whether participants of the studies were SGM or non-SGM (e.g., bystanders/general population). To capture relevant literature, we used specific keywords with Boolean operators, ensuring a full exploration of the selected databases. To maintain conceptual separation from cyberbullying and related individual-level aggression, we did not include cyberbullying-specific keywords in the search string and excluded studies that primarily operationalized the phenomenon as cyberbullying during screening. Below is an exemplified representation of the search strategy executed in the five databases:

cyberhat* OR “cyber hat*” OR Cyber-hat* OR “online hat*” OR “online discrimin*” OR “hat* online” OR “digit* hat*” OR “social media hat*” OR “online offen*” OR “online harass*” OR “online victim*” OR (“hat* Speech” AND online) [TOPIC CLUSTER];

AND

“sexual and gender minorit*” OR “sexual and gender divers*” OR lgb* OR Sogie OR “sexual orientation” OR “sexual minorit*” OR “sexual diversit*” OR “same-sex relationship” OR Lesbian* OR Gay* OR Bisex* OR Queer OR Homophob* OR Biphob* OR Transphob* OR “gender identit*” OR “gender divers*” OR “gender minorit*” OR Transgender OR Transexual OR “gender varian*” OR gender-variant OR gender-diverse OR two-spirit OR agender [TARGET CLUSTER] .

Our search strategy involved a systematic cross-referencing of terms from these two distinct clusters. Specifically, we combined every term from the “target” cluster with every term from the “topic” cluster in order to maximize the retrieval of relevant studies. Inclusion and exclusion criteria to apply throughout the screening process were decided a priori.

Eligibility and Exclusion Criteria

Five eligibility criteria were pre-specified, and studies were included only if they met all of the following: (a) publication in a peer-reviewed scientific journal; (b) English-language reporting; (c) examination of OHS or closely related constructs, defined as the online dissemination of discriminatory or offensive content targeting social groups (rather than individuals); (d) OHS specifically directed toward SGMs; and (e) a quantitative design (or mixed methods with extractable quantitative outcomes) involving human participants. We restricted our review to articles employing quantitative or empirical research designs to maximize methodological consistency and cross-study comparability, as peer-reviewed journal articles are more likely to provide the minimum reporting detail needed for reliable synthesis (e.g., sampling and recruitment procedures, measures and operational definitions, analytic strategy, and outcome reporting). This was especially important given our review objectives, which required direct comparisons of how OHS toward SGM is defined and conceptualized, how studies are designed, and how key constructs are operationalized across the literature. This allowed for a more coherent synthesis of findings and a more focused examination of the processes under investigation. Systematic reviews, meta-analyses, and theoretical articles were excluded, as well as certain publication types that did not meet our standards, such as conference papers, PhD dissertations, books, book chapters, and unpublished manuscripts. Additionally, studies that focused on offline forms of hate speech or cyberbullying were also disregarded, as these did not align with the primary objective of this review.

The search returned 1,178 articles. After removing duplicates, 341 articles were screened based on title and abstract (Figure 1). Two independent reviewers (i.e., M.M. and N.D.B.) conducted the screening process. Any discrepancies in selection were resolved through discussion and, when necessary, consultation with a third reviewer (i.e., S.C.). Full-text screening was performed for all potentially eligible studies based on the abstract review. Articles that did not meet the inclusion criteria after full-text assessment were excluded, and the reasons for exclusion were documented. This screening process resulted in 13 articles to be included in this review. The entire screening process was carried out with the support of the online software Rayyan (Ouzzani et al., 2016). To assess the consistency of the screening process, we calculated inter-rater reliability using Cohen’s Kappa (κ). This measure helped evaluate the level of agreement between the two reviewers beyond chance. A κ value of .89 was obtained, indicating an excellent level of agreement between the reviewers (McHugh, 2012).

Figure 1.

PRISMA flow diagram of the study selection process.

Quality Assessment

The inter-rater reliability analysis was conducted following the methodology outlined in Kmet et al. (2004), using the scores assigned by two independent reviewers to evaluate the quality of studies across 14 items (details are provided in Supplemental Material 2). The percentage agreement was calculated as the proportion of identical scores across all items, while Cohen’s Kappa was used to assess the level of agreement. The total agreement percentage between the two reviewers was 87.36%, indicating a high level of consistency. Cohen’s Kappa coefficients further confirmed substantial agreement (κ = .76).

Results

RQ1: Sample Characteristics, Study Designs, and Operationalizations of OHS Targeting SGM Groups

Sample Characteristics

Regarding the first RQ (RQ1) (i.e., identifying the key characteristics of studies on OHS targeting SGM groups and understanding how OHS has been defined and operationalized), findings show that research on OHS targeting SGM groups is still in its early stages, with studies being published only recently between 2019 and 2024. The 13 studies in this systematic review primarily collected data from Europe and North America. Some focused on single countries, such as Italy (Ieracitano et al., 2024; Mancini & Imperato, 2020), Austria (Schäfer et al., 2024), Germany (Obermaier & Schmuck, 2022; Obermaier et al., 2023), Cyprus (Baider & Anaxagorou, 2022), the USA (Costello et al., 2019; Fisher et al., 2024), and Spain (Martínez-Bacaicoa et al., 2023). Four studies used cross-national samples: Two within Europe, one across Germany, Austria, and Switzerland (Schäfer et al., 2022), and another including Belgium, the Netherlands, Ireland, and the UK (Van Houtven et al., 2024). The other two studies included participants from both Europe and beyond: Keighley (2022) drew from France, Italy, Germany, the UK, the USA, Canada, and Hong Kong, while McInroy et al. (2024) included participants from the UK, the USA, and Canada.

Across the 13 included studies, sample sizes ranged from N = 48 to N = 2,316, with most studies recruiting several hundred participants. Samples were primarily community-based adolescents and young adults (approximately 13–36 years), complemented by several adult cohorts extending to 67–69 years and one experimental study with a higher mean age (≈ 47 years). Importantly, none of the studies involved clinical populations. In terms of age groups, five studies focused exclusively on adults (Baider & Anaxagorou, 2022; Ieracitano et al., 2024; Mancini & Imperato, 2020; Martínez-Bacaicoa et al., 2023; Van Houtven et al., 2024), whereas four targeted adolescents and young adults (Costello et al., 2019; Keighley, 2022; McInroy et al., 2024; Obermaier & Schmuck, 2022). Only one study specifically examined minors (Fisher et al., 2024).

Regarding sexual orientation and gender identity, four studies recruited SGM-only samples (Fisher et al., 2024; Keighley, 2022; McInroy et al., 2024; Van Houtven et al., 2024), while the remaining studies relied on heterogeneous/general-population samples, typically female-majority or approximately gender-balanced. Notably, one experiment examining OHS targeting transgender people excluded 16 transgender participants because ethical considerations precluded exposing individuals to hate speech directed at a group to which they belong (Schäfer et al., 2024). One study also focused on a specific SGM subgroup (lesbian, gay, and bisexual participants; Van Houtven et al., 2024). All the relevant study characteristics are reported in Table 1.

Table 1.

Information Extracted From the Included Studies.

Authors	Year	Country	Participants				Study design	OHS target	Exposure/perpetration	Measures	Main findings
Authors	Year	Country	Minority or majority group	N	Age	Gender	Study design	OHS target	Exposure/perpetration	Measures	Prevalence	Predictors of OHS	Impact of OHS	Reaction of OHS
Baider and Anaxagorou	2022	Cyprus	NS	95 survey 40 biosignal	Adults (over 18)	—	Experimental	Sexual Orientation	Exposure	Biosignal measures (e.g., heart rate, breathing, skin-conductance response) for physiological responses to hate content.	—	—	—	Homophobic content was rejected as morally unacceptable but did not produce significant physiological changes like blood pressure or pulse variations.
Costello et al.	2019	USA	Heterogeneous	968	Youths (15–36)	50% women 50% men	Correlational	Sexual orientation	Exposure	Ad hoc questions assessing exposure to online hate material.	—	Higher social network use, defending others, engaging with offensive content, and discussing private matters online were linked to increased risk; living in the South or rural areas also increased risk.	—	—
Fisher et al.	2024	USA	Only LGBTQ+	778	Adolescents (14–18)	204 women 158 men 44 non-binary	Correlational	Sexual orientation and gender identity	Exposure	Adaptation of the Online Victimization Scale (Tynes et al., 2010) to evaluate personal and vicarious exposure to online discrimination.	Exposure: 85.71% of SGMs adolescents	__	Depression, anxiety, substance use	__
Ieracitano et al.	2024	Italy	Heterogeneous	48	Youths (18–30)	63% women 37% men	Correlational	Sexual orientation	Exposure	Moral Reasoning in the context of OHS: ad hoc measure adapted from the DIT-2 (Rest et al., 1999); Hate Speech Moral Disengagement: was measured using an adaptation of the Cyber Moral Disengagement Scale (Berrone, 2015).	__	__	__	Participants mainly used Post-conventional and Maintaining Norms reasoning in response to homophobic OHS, while Personal Interest was least used.
Keighley	2022	UK (155) France (6.9%), USA (1.7%), Italy (0.6%), Germany (0.6%), Canada (1.2%), Hong Kong (0.6%)	Only LGBTQ+	175	Adolescents and Youths (13–25)	110 female, 37 male, 7 agender, 1 demi-boy 2 demi-girl 14 non-binary, 14 gender-fluid 2 prefer not to say	Correlational	Sexual orientation and gender identity	Exposure	Ad hoc questions divided into 3 sections: (A) nature of LGBTQ+ online hate; (B) experiences of support services; (C) expectations of support services.	__	__	Depression, anxiety, mistrust, and concealment	—
Mancini and Imperato	2020	Italy	Heterogeneous	357	Adults (18–69; M_age = 26.07)	125 males, 231 females (1 missing)	Correlational	Sexual orientation	Exposure	Online Discrimination (personal, mediated, and vicarious) was measured through the POSDS—adaptation of PORS (Keum & Miller, 2017).	Exposure rarely perceived	OHS visibility was higher among users with more SGM contacts and those exploring their identity; sexual minority status and female gender showed positive associations, while age showed a weak negative association.	—	—
Martínez-Bacaicoa et al.	2023	Spain	Heterogeneous	2316	Adults (over 18)	69% women 31% men	Correlational	Sexual orientation and gender identity	Perpetration	Technology-facilitated gender- and sexuality-based violence (TFGSV) Perpetration: developed using previous measures to assess three types of gender- and sexuality-based violence (e.g., Gámez-Guadix & Íncera, 2021; Gámez-Guadix et al., 2022, 2023).	Perpetration: 2,3-2,7%	Men and younger participants were slightly more likely to perpetrate OHS, though substantial proportions of women and non-binary individuals also reported engaging in it.	—	—
McInroy et al.	2024	UK, USA, Canada	Only LGBTQ+	1179	Adolescents and Youth (14–24)	20 (1.7%) gender fluid 13 (1.1%) genderqueer 3 (0.3%) gender non-conforming 24 (2%) trans-man/trans-masculine 40 (3.4%) two-spirit 6 (0.5%) woman 1 (0.1%) prefer not to say	Correlational	Sexual orientation and gender identity	Exposure	Digital Vignette Scenarios: vignette with five depictions of real anti-LGBTQ+ microaggressions from social media; Frequency of microaggression exposure.	Exposure: 94,1%	—	—	—
Obermaier et al.	2023	Germany	Heterogeneous	140–130	NS (M_age = 23)	60% female 40% male	Experimental	Sexual orientation	Exposure	Vignette: fictious Facebook post that included hateful expressions against LGBTQIA+ Perceived incivility (Kenski et al., 2020); Perceived personal responsibility (Leonhard et al., 2018); Intention of bystander intervention (Bartlett and Krasodomski-Jones, 2015; Leonhard et al., 2018).	—	—	—	Greater perceived incivility among bystanders was associated with stronger personal responsibility and higher intentions to intervene or encourage others to act.
Obermaier and Schmuck	2022	Germany	Heterogeneous	591	Youths (16–25)	54% female 46% male	Correlational	Sexual orientation and gender identity	Exposure	Online hate speech victimization was measured by inquiring how often participants had been targets of OHS in general. Frequency of exposure to online hate speech.	—	Identifying as a sexual minority is the strongest predictor of OHS victimization; political or activist engagement, frequent exposure to hateful content, and low digital media literacy also increase risk.	—	—
Schäfer et al.	2024	Austria	Only cisgender	1285	NS (M_age = 47.43)	51% women 49% men	Experimental	Gender Identity	Exposure	Six different fictitious Facebook newsfeeds including a post and comments underneath the post. The amount of hate speech was manipulated across three levels (none/few/many).	—	—	Exposure to transphobic OHS was not linked to stereotypes or social distancing, but right-wing participants showed reduced social distancing after exposure; counter-speech increased stereotypes and social distancing among right-wing participants compared to hate speech alone.	__
Schäfer et al.	2022	Austria, Germany, Switzerland	Heterogeneous	920	NS	56% female 44% male	Experimental	Sexual orientation	Exposure	Six different fictitious Facebook newsfeeds including a post and comments underneath the post. Participants were exposed to one of three conditions: Hate speech only; Neutral comments; Hate speech followed by counter-speech.	—	—	Exposure to OHS was associated with a decline in perceived social cohesion and greater social distancing.	Participants with neutral or negative attitudes toward SGM individuals were more likely to agree with hateful comments, especially after exposure to OHS targeting SGM people.
Van Houtven et al.	2024	Belgium, Netherlands, Ireland, UK	LGBTQ+ (subgroup LGB)	225	Adults (18–67)	47.6% female 45.8% male 3.6% non-binary 2.7% (preferred not to say)	Experimental	Sexual orientation	Exposure	Six fictitious Instagram posts with 2 (mildly vs. extremely severe hate speech) × 3 (no counter-speech, counter-speech by a minority member, or counter-speech by a majority member) conditions.	—	—	Exposure to more severe anti-SGM posts increased participants’ identity threat, which in turn increased avoidance of non-LGBTQIA+ people)	—

Note. DIT-2 = Defining Issues Test 2; NS = Not specified; OHS = Online hate speech; PORS = Perceived Online Racism Scale; POSDS = Perceived Online Sexual Discrimination scale; SGM = sexual and gender minority.

Study Designs

The studies included in this systematic review employed a range of methodological approaches, reflecting the complexity of researching OHS. Most used cross-sectional correlational designs, relying primarily on online surveys to collect quantitative data (e.g., Ieracitano et al., 2024; Mancini & Imperato, 2020; McInroy et al., 2024; Obermaier & Schmuck, 2022). In these studies, OHS exposure was typically measured using Likert-type frequency items assessing how often participants had witnessed hate speech online (e.g., Baider & Anaxagorou, 2022; Costello et al., 2019; Fisher et al., 2024; Mancini & Imperato, 2020); in one case, Fisher et al. (2024) adapted the Online Victimization Scale (Tynes et al., 2010) to assess recent discrimination on social media, including vicarious experiences involving LGBTQ+ people. Several cross-sectional studies also incorporated open-ended questions (e.g., Fisher et al., 2024; Martínez-Bacaicoa et al., 2023) or paired self-report measures with interviews (e.g., Keighley, 2022). Recruitment strategies varied and included social media advertising (Fisher et al., 2024; Keighley, 2022; McInroy et al., 2024), school-based recruitment (Ieracitano et al., 2024; Martínez-Bacaicoa et al., 2023), snowball sampling (Keighley, 2022; Mancini & Imperato, 2020), and recruitment via a specialized panel company (Obermaier & Schmuck, 2022). Only one study operationalized perpetration (Martínez-Bacaicoa et al., 2023), using open-ended responses to distinguish passive (e.g., sharing degrading content) from active (e.g., posting degrading content) perpetration related to sexual or gender identity over the past year.

Other studies used experimental designs to examine responses to anti-SGM OHS by manipulating (a) the type/severity/amount of hate content, (b) the target of hateful messages, and (c) counter-speech (presence and counter-speaker identity). Experiments typically relied on standardized simulated social media stimuli (e.g., memes, tweets, Facebook posts/newsfeeds). Baider and Anaxagorou (2022) combined questionnaires and interviews with meme/tweet manipulations and uniquely added physiological measures (blood pressure, heart rate). Obermaier et al. (2023) exposed SGM participants to a fictitious Facebook post plus a discriminatory comment and assessed perceived incivility, personal responsibility, and bystander intervention intentions. Schäfer et al. (2024) used simulated Facebook news feeds about transgender people, varying the comments (neutral vs. hate vs. hate + counter-speech), while Schäfer et al. (2022) recruited a heterogeneous sample (heterosexual/cisgender and SGM participants) and manipulated both hate volume and target group. Van Houtven et al. (2024) examined sexual minority (SM) participants’ responses to homophobic OHS by manipulating hate severity and counter-speech presence/source (minority vs. majority speaker).

Defining and Operationalizing OHS Targeting SGMs

Except for Keighley’s (2022) study, which underscores the risks of narrowly defining OHS and neglecting its broader and more subjective dimensions, the remaining literature employs a variety of definitions. Further details are provided in Supplementary Material 1, which summarizes how OHS is conceptualized across the 13 studies reviewed.

Despite variations in terminology, recurring themes include abuse, harm, violence, hostility, hatred, stigmatization, harassment, intimidation, insult, and discrimination, often conveyed through degrading or dehumanizing discourse (Costello et al., 2019; McInroy et al., 2024; Obermaier & Schmuck, 2022; Obermaier et al., 2023; Schäfer et al., 2024; Van Houtven et al., 2024). A key feature distinguishing OHS from other forms of online aggression (e.g., cyberbullying or cyberstalking) is its focus on identity-based targeting (e.g., Costello et al., 2019; Ieracitano et al., 2024; Keighley, 2022; McInroy et al., 2024). However, only two studies (Baider & Anaxagorou, 2022; Mancini & Imperato, 2020) did not explicitly refer to identity-based targeting in their definitions.

Some studies add further nuance. Intentionality is highlighted in three studies (Ieracitano et al., 2024; Martínez-Bacaicoa et al., 2023; Van Houtven et al., 2024), while McInroy et al. (2024) uniquely acknowledge that OHS may also be unintentional. Others emphasize the potential harm OHS can inflict on marginalized groups as an important aspect of the operationalization (e.g., Keighley, 2022; Schäfer et al., 2022, 2024). Finally, only a few definitions address the broader social implications: Obermaier and Schmuck (2022) stress how OHS violates public norms of democratic discourse, and Schäfer et al. (2024) underline its threat not only to individuals but to society as a whole.

In addition to definitions, the reviewed studies varied widely in examining whether OHS targeting SGMs was based on sexual orientation, gender identity, or gender expression. Five studies explored OHS directed at people based on both their gender identity and sexual orientation (Fisher et al., 2024; Keighley, 2022; Martínez-Bacaicoa et al., 2023; McInroy et al., 2024; Obermaier & Schmuck, 2022). However, most studies focused solely on OHS related to sexual orientation (Baider & Anaxagorou, 2022; Costello et al., 2019; Ieracitano et al., 2024; Mancini & Imperato, 2020; Obermaier et al., 2023; Schäfer et al., 2022; Van Houtven et al., 2024). Only one study specifically investigated transphobic OHS (Schäfer et al., 2024).

RQ2: Prevalence and Risk Factors of OHS Targeting SGM Groups

Prevalence

Prevalence estimates for the second RQ (RQ2) were examined exclusively in correlational studies. Among those, only a small subset provided relevant data on the prevalence, focusing on exposure (Fisher et al., 2024; Mancini & Imperato, 2020; McInroy et al., 2024) and perpetration (Martínez-Bacaicoa et al., 2023). Ieracitano et al. (2024) reported aggregate prevalence for OHS exposure without SGM-specific breakdown, and Keighley (2022) provided no prevalence data.

Regarding OHS exposure, Fisher et al. (2024) found that 85.7% of SGM adolescents (M_age = 16.05) faced identity-based OHS on social media. McInroy et al. (2024) reported digital microaggressions among SGM young adults (18–24), with 94.1% exposed, 75.7% facing OHS at least monthly, and 50.5% weekly. Mancini and Imperato (2020), studying a broader age range (18–69, M_age = 26.07), observed that non-heterosexual participants (5.3% of the sample) were significantly more likely to be exposed to OHS than people self-identifying as exclusively or predominantly heterosexual (93.5% of the sample). Finally, Martínez-Bacaicoa et al. (2023) examined OHS perpetration among SM and transgender participants, with 2.7% and 2.3%, respectively, reporting perpetration.

Risk Factors of OHS

Three studies (Costello et al., 2019; Mancini & Imperato, 2020; Obermaier & Schmuck, 2022) identified a range of intersecting individual, behavioral, and contextual factors associated with OHS exposure. SM identity emerged as a key predictor in two studies. Obermaier and Schmuck (2022), in a study involving a heterogeneous group of adolescent and young adult Internet users, found that identifying as a SM was the strongest predictor of being exposed to OHS. Similarly, Mancini and Imperato (2020) reported a positive association between SM identity and OHS exposure, also noting that exposure was more likely among people who had more SGM contacts online and were actively exploring their own sexual identity.

Several behavioral factors were associated with OHS exposure. Obermaier and Schmuck (2022) identified political or activist engagement, frequent exposure to hateful content, and low digital media literacy as risk factors. These elements jointly increase visibility and vulnerability in online spaces. Costello et al. (2019) found that in a heterogeneous group of adolescent and young adult Internet users living in the USA, behaviors such as intensive social network use, defending others online, engaging with offensive content, and discussing private matters online were also positively associated with OHS exposure.

Regarding contextual factors, Costello et al. (2019) showed that people living in Southern USA or in rural areas were significantly more likely to be targeted. In contrast, demographic variables such as age, gender, education, migration background, and religion (Obermaier & Schmuck, 2022), as well as time spent online, ethnicity, and levels of social connectedness (Costello et al., 2019), were not consistently associated with SGM-specific OHS. However, Mancini and Imperato (2020) found that gender (female) showed a weak positive association with OHS exposure, while age was weakly and negatively correlated.

Regarding OHS perpetration, Martínez-Bacaicoa et al. (2023) reported higher prevalence rates among men (4.3%) and non-binary participants (7.9%, even though non-binary participants represented 1% of the sample) compared to women (1.9%), with the highest prevalence observed among participants aged 35 to 44 (4.9%). Similar gender- and age-based disparities were identified for OHS targeting transgender people, with higher rates among men (3.9%) and non-binary participants (8.3%) than among women (1.5%), and a peak prevalence among participants aged 35 to 44 (4.5%).

RQ3: The Impact of OHS Targeting SGM Groups on Well-Being, Health Behaviors, and Social Attitudes

To address the third RQ (RQ3) on the impact of OHS, studies were grouped into two categories: The first, examining effects on psychological well-being and minority stress, involved exclusively SGM participants; the second, investigating its influence on social attitudes, included one study with a heterogeneous sample (Schäfer et al., 2022), one with only cisgender participants (Schäfer et al., 2024), and one with SGM participants (Van Houtven et al., 2024).

Psychological Well-Being and Health Behaviors

Two correlational studies and one experimental study analyzed the psychological consequences of OHS on SGMs targets. The two correlational studies reported negative effects on mental health, such as depression and anxiety (Fisher et al., 2024; Keighley, 2022), substance use (Fisher et al., 2024), loss of trust, emotional harm (Keighley, 2022), and identity concealment (Keighley, 2022). Interestingly, Fisher et al. (2024) found that the association between exposure to OHS on social media and risk for depression, anxiety, and substance use was moderated by users’ perceptions of social media: Among users experiencing high levels of discrimination, those who described social media as a space of belonging and support for the SGM community reported worse mental health outcomes than those who perceived it as unwelcoming.

In their experimental study, Van Houtven et al. (2024) found that exposure to severe OHS (via simulated Instagram posts) significantly increased perceived identity threat, defined as feelings of degradation, discrimination, or threat due to hostile messages, while counter-speech, defined as online responses to challenge, refute, or counteract OHS, had no mitigating effect.

Social Attitudes

Three experimental studies investigated the impact of OHS on social attitudes. In a heterogeneous sample including both SGM and non-SGM participants, Schäfer et al. (2022) found that exposure to experimentally manipulated OHS comments targeting sexual minorities reduced perceived social cohesion, defined as the sense of individuals and groups being integrated into a larger collective. In another experimental study with only cisgender participants, Schäfer et al. (2024) found that exposure to transphobic OHS was not significantly associated with explicit and implicit stereotypes, or socially distancing attitudes (i.e., people’s lack of willingness to accept transgender people as part of society and everyday life). However, political orientation moderated the effect: Among right-wing participants, exposure to hate speech was paradoxically associated with reduced social distancing. The study also explored the role of counter-speech as a moderator of the relationship between stereotypes (both implicit and explicit) and social distancing. They found that after the experimental exposure to counter-speech to defend transgender people, right-wing participants expressed stronger stereotypes and greater social distancing than those exposed to hate speech alone.

The experimental study by Van Houtven et al. (2024) involving SGM participants found that exposure to severe OHS (i.e., OHS that is explicitly hostile in tone including offensive language or threats to targeted group) was associated with higher identity threat and, in turn, with SGM participants’ intention to avoid cisgender and heterosexual people. This was in contrast to mild OHS (i.e., OHS including indirect or nuanced expressions that convey stereotypes and disparaging remarks). The study also examined the effects of counter-speech on the perception that one’s social group is portrayed in a harmful, threatening, or demeaning manner. Regardless of the source of counter-speech (minority vs. majority group members) or the severity of the OHS, counter-speech exposure did not significantly affect the perceptions of negative group representation. However, counter-speech did influence perceived identity threat in mild OHS scenarios. In those cases, counter-speech from a majority group member significantly reduced identity threat, an effect not observed with severe OHS.

RQ4: Bystanders’ Reactions and Responses to OHS Targeting SGM Groups

The fourth RQ (RQ4) addressed how people react when exposed to OHS targeting SGMs. The following studies, based on general population samples and not exclusively SGM participants, examined responses in terms of acceptance or rejection of hate content, reaction time, moral reasoning, intentions to intervene, and the perceived effectiveness of counter-speech.

Baider and Anaxagorou (2022) conducted a mixed-methods experimental study combining questionnaires, interviews, and biosignal tracking to examine responses to various forms of hate speech (homophobic, sexist, and racist). Homophobic content was widely rejected and recognized as morally unacceptable by most participants; however, when biosignal measures (pulse and blood pressure) were used as an objective way to capture emotional and stress responses beyond self-reports, they did not show significant physiological changes, such as variations in pulse or blood pressure, revealing a possible discrepancy between explicit moral condemnation and embodied responses. Schäfer et al. (2022) found that pre-existing attitudes toward SGMs shaped participants’ responses: Those with neutral or negative attitudes were more likely to agree with hateful comments, particularly when exposed to OHS targeting SGM people. Ieracitano et al. (2024) examined how people judge homophobic OHS by asking participants to evaluate a realistic scenario in which a celebrity was targeted with homophobic hate content. Using questions adapted from a standard moral-judgment tool (Defining Issues Test [DIT-2]; Rest et al., 1999), the study distinguished three straightforward ways people can make such judgments: principles-based reasoning (deciding based on broad values like fairness, equality, and human rights), rules-and-order reasoning (deciding based on rules, authority, and what is acceptable for maintaining social order), and self-focused reasoning (deciding based on personal consequences and self-interest). Because these reasoning styles were measured in response to one specific vignette, they were treated as context-dependent ways of thinking in that moment, not stable traits. Overall, participants rarely used principles-based reasoning; instead, their evaluations were driven mainly by rules-and-order concerns, indicating that judgments of homophobic OHS were shaped more by norms and rule compliance than by abstract ethical principles. Within this pattern, men relied more on self-focused reasoning, whereas women relied more on rules-and-order reasoning. Finally, the authors identified moral disengagement, the mental strategies people use to justify or downplay harm, as a key mechanism linking personal values to these judgments.

Finally, Obermaier et al. (2023) examined how perceived incivility of OHS influences bystander responses (i.e., people exposed to OHS targeting SGM). Results indicated that greater perceived incivility of OHS among bystanders was positively associated with personal responsibility and intentions to intervene or encourage others to act. However, homophobic hate speech was perceived as less uncivil than misogynistic or ethnic hate speech.

Discussion

This systematic review examines OHS targeting SGMs, a social group facing high risks of discrimination, violence, harassment, and social exclusion (Katz-Wise & Hyde, 2012; Powell et al., 2020). A total of 13 quantitative studies published since 2019 was analyzed, indicating that research on this topic remains in its early stages.

Overall, the findings of this review can be grouped into four main thematic areas: (RQ1) studies describing the main characteristics of the examined research and the way OHS is defined and operationalized; (RQ2) studies addressing the prevalence and the factors that predict exposure to, or the active production of, hateful content (i.e., perpetrators); (RQ3) studies examining the effects of OHS exposure on psychological well-being, health behaviors, and social attitudes among both SGMs and non-SGM users; and (RQ4) studies exploring how SMG and non-SGM people respond to OHS against SGMs.

RQ1: Study Characteristics and Operationalizations of OHS Targeting SGM Groups

Across the included studies, a particularly relevant characteristic was the distinction concerning the sexual and gender identity of the participants. The four studies that focused on SGM participants mainly examined the psychological and social consequences of OHS exposure. In contrast, the nine studies drawing on general population samples, without focusing specifically on SGM participants, were primarily interested in how exposed people perceive OHS and whether they choose to intervene in such situations.

In the broader hate speech and cyberhate literature, there is no universally accepted definition of OHS (Kansok-Dusche et al., 2023; MacAvaney et al., 2019). Within the 13 studies included in this review, this definitional pluralism was reflected in the use of terms ranging from “online hate speech” to “digital microaggressions,” “vicarious discrimination,” and online “targeted gender- and sexuality-based violence.” These works were included because, despite variations in wording, their operational definitions substantially overlap with the conceptual boundaries of OHS. For the purposes of this review, we therefore adopt “OHS” as an umbrella term encompassing these perspectives, generally referring to the online dissemination of derogatory expressions, via posts, comments, videos, or stories, targeting individuals or groups on the basis of characteristics such as ethnicity, gender, sexual orientation, religion, disability, and appearance.

Across the included studies, three operational components appeared most consistently. First, the mode of expression included public or semi-public digital spaces and formats such as comments, posts, stories, memes, and videos (Costello et al., 2019; Schäfer et al., 2022; Van Houtven et al., 2024). Second, the content involved degrading, hostile, or discriminatory material that may incite, propagate, or normalize hostility or discrimination (Costello et al., 2019; McInroy et al., 2024; Obermaier & Schmuck, 2022; Schäfer et al., 2024). Third, the targeting criterion included sexual orientation, gender identity, and/or gender expression (Fisher et al., 2024; Ieracitano et al., 2024; McInroy et al., 2024). Based on the literature synthesized in this systematic review, OHS targeting SGM could be operationalized as

“The online dissemination in public or semi-public digital spaces of degrading, hostile, or discriminatory content that incites, propagates, or normalizes hostility or discrimination against individuals or groups based on their sexual orientation, gender identity, or gender expression. This form of expression is primarily content-driven; it is expressed through text, images, videos, or other digital formats.”

It is important to note that, although often used interchangeably in the broader literature on digital aggression, OHS and bias-based online harassment or victimization represent conceptually distinct, though overlapping, forms of identity-based aggression in digital environments. Bias-based online harassment differs because it entails targeted and hostile actions, such as threats, doxing, cyberstalking, and coordinated attacks, explicitly motivated by prejudice toward the victim’s identity (Bedrosova et al., 2024; Powell et al., 2020). It is defined not only by the presence of hate-based content, but by the intentional infliction of harm, the individualization of the target, and the power dynamics involved in repeated victimization when it becomes cyberbullying (Fulantelli et al., 2022). Taken together, online harassment constitutes a behavioral pattern that extends beyond speech to include a wider spectrum of digital violence. Distinguishing OHS from broader forms of online harassment, while also clarifying their areas of overlap, is crucial for advancing both research and intervention. Establishing a shared definition of OHS is particularly important in light of the distinct perpetrator intents, victim experiences, legal implications, and psychological outcomes associated with this form of online violence (Brown, 2017; Fulantelli et al., 2022; Kansok-Dusche et al., 2023; Kwan et al., 2020).

RQ2: Prevalence and Risk Factors of OHS Targeting SGM Groups

In the included correlational studies, only a subset reported data relevant to prevalence (Fisher et al., 2024; Mancini & Imperato, 2020; Martínez-Bacaicoa et al., 2023; McInroy et al., 2024). However, findings consistently show large differences between general and SGM-focused samples. Research conducted exclusively with SGM participants (Fisher et al., 2024; McInroy et al., 2024) reports extremely high exposure rates to OHS (often above 85%), while studies based on general population samples show lower overall prevalence, though SGM respondents within these samples remain significantly more exposed than heterosexual participants. Studies by Costello et al. (2019) and Obermaier and Schmuck (2022) identified risk factors associated with OHS exposure. Their findings suggest that OHS often targets SGM people who are highly visible, such as those who are openly SGM or actively engaged in advocacy, and those who hold multiple marginalized identities. Notably, OHS is often triggered also by acts of resistance or expressions of solidarity toward victims of hate, potentially creating a hostile feedback loop in which both marginalized victims and their allies are punished. Furthermore, the prevalence of OHS appears to be shaped by the quality of platform moderation and the broader sociopolitical climate, suggesting that digital hate is not only an interpersonal issue but one deeply rooted in systemic structures and cultural contexts (Hatzenbuehler et al., 2010). Mancini and Imperato (2020) offered an interesting insight into OHS exposure by suggesting that this experience may depend on the personal tendency to notice it. For example, they found that people exploring their sexual identity and those with SGM friends are more likely to notice OHS. This implies that exposure is not only about frequency but also about awareness shaped by personal and social factors.

Only one correlational study specifically examined OHS perpetration (Martínez-Bacaicoa et al., 2023), suggesting, consistent with prior research on anti-SGM cybervictimization, that men were slightly more likely to engage in such behavior (Blaya & Audrin, 2019; Hilte et al., 2023). However, a substantial proportion of women and non-binary participants also reported perpetrating OHS. These findings suggest that the correlates of OHS perpetration may differ from those typically associated with bias-based online victimization. However, as an additional major result, the profiles of perpetrators remain a relatively underexplored area in the literature on OHS targeting SGM individuals.

RQ3: The Impact of OHS Targeting SGM Groups on Well-Being, Health Behaviors, and Social Attitudes

Across studies included in this review, exposure to OHS was consistently associated with poorer psychological and social adjustment among SGM participants. The direction of these associations is in line with broader evidence linking identity-based harassment and discrimination among SGM groups, both offline and online, to psychological distress (Bishop et al., 2023; Fish et al., 2023; Mulvey et al., 2018; Russell et al., 2012). Yet, this review helps specify how anti-SGM OHS may operate as a minority stress exposure in digital contexts and which proximal processes appear most salient. Specifically, OHS exposure has been associated with minority stressors such as the concealment of one’s SGM identity (Keighley, 2022) and experiences of degradation, discrimination, and threat (Van Houtven et al., 2024). These can be conceptualized as proximal minority stressors, central mechanisms which, according to the Minority Stress model (Meyer, 2003), affect the well-being of SGM people. Indeed, OHS exposure has also been associated with a range of negative mental health outcomes, including depression, anxiety, substance use (Fisher et al., 2024; Keighley, 2022), emotional harm, and exhaustion (Keighley, 2022). These associations have been found both in correlational studies assessing OHS exposure in real-world situations based on participants’ personal experiences (Fisher et al., 2024; Keighley, 2022) and in experimental studies examining the psychological impact of exposure to simulated online anti-SGM posts (e.g., Van Houtven et al., 2024). These findings are consistent with the broader literature documenting that exposure to online violence is associated with greater mental distress among SGM population (Berger et al., 2022; Carson et al., 2024; Marciano & Antebi-Gruszka, 2020; Tao & Fisher, 2023).

In addition to psychological effects, OHS exposure has also been associated with negative behavioral outcomes in the SGMs population. For example, one correlational study showed that OHS exposure was associated with withdrawal from both online and offline spaces, leading to high risk for social isolation and disruption of interpersonal relationships (Keighley, 2022). This finding was also confirmed by an experimental study showing that exposure to anti-SGM posts increased participants’ reluctance to engage with members of majority groups (Van Houtven et al., 2024).

The impact of OHS exposure on non-SGM people has been less thoroughly investigated. However, findings by Schäfer et al. (2024) suggest that these effects did not hold when participants were exposed specifically to transphobic OHS. Taken together, this line of evidence remains limited and requires further empirical validation to clarify the conditions under which OHS influences social attitudes among non-SGM populations.

Given the variety of study designs, it is useful to consider what each approach contributes and what it cannot resolve. Observational studies offer ecological validity and capture how OHS co-occurs with broader minority stress in everyday contexts; however, they are vulnerable to confounding and selection processes (e.g., concurrent offline discrimination, differential platform engagement, pre-existing distress), limiting causal inference. Experimental studies strengthen internal validity by manipulating exposure and standardizing stimuli, allowing clearer inference about short-term, proximal responses to OHS content (e.g., perceived identity threat). Simulated exposures may not fully reflect the cumulative, interactive, and algorithmically mediated nature of OHS encounters in naturalistic online environments. Taken together, evidence across designs supports a link between OHS exposure and poorer well-being, while underscoring the need for longitudinal and mixed-methods research to clarify directionality and longer-term effects.

RQ4: Bystanders’ Reactions and Responses to OHS Targeting SGM Groups

A final line of research in this systematic review investigated how people react when exposed to OHS. In general, OHS targeting SGMs was recognized by most participants as morally unacceptable (Baider & Anaxagorou, 2022; Obermaier et al., 2023). However, findings on how this form of hate speech compares to others remain inconsistent. Some evidence suggests that anti-SGM OHS is more accepted than sexist or ethnic hate speech (Obermaier et al., 2023), while other research indicates it is less accepted than sexist and anti-immigrant OHS but condemned to a similar extent as racist OHS (Baider & Anaxagorou, 2022). This variation may depend on personal attitudes toward SGM people. Schäfer et al. (2022) in their experimental study showed that neutral or negative attitudes toward SGMs were more likely to agree with hateful comments against SGM people. The acceptability of OHS is closely tied to moral reasoning, as individuals must assess what should be considered morally condemnable. This was the focus of Ieracitano et al. (2024), who conducted a study examining the types of moral reasoning people use when evaluating the acceptability of homophobic OHS. Their findings indicate that acceptability or non-acceptability often reflects either adherence to prevailing social or cultural norms (i.e., maintaining norms reasoning) or a commitment to individually held interpretations of universal principles of human rights, justice, and equality (i.e., post-conventional reasoning). Notably, the study also found that, among men, the acceptability of OHS may be associated with personal interest reasoning, suggesting that the decision to perpetrate OHS may also depend on negative or positive consequences of the action.

The acceptability of OHS targeting SGMs may play a crucial role in understanding the largely understudied issue of bystander intervention (i.e., exposed people) in such contexts. To date, only one study (Obermaier et al., 2023) has shown that, among bystanders, high levels of perceived incivility of OHS toward SGMs were positively associated with greater personal responsibility and stronger intentions to intervene or encourage others to act to stop the behavior. These findings align with Latané and Darley’s (1970) model of bystander intervention, which states that two key prerequisites for helping behavior are noticing the event and interpreting it as an emergency or unjust situation that requires action. Future research should explore how individual and contextual factors influence each step of bystander intervention in response to OHS against SGMs (i.e., noticing the event, interpreting it as harmful, assuming responsibility, knowing how to help, and deciding to act).

Limitations

This systematic review presents certain limitations that should be acknowledged. First, the inclusion criterion requiring studies to be published in English led to the exclusion of research conducted in other languages, thereby limiting the comprehensiveness of the review and potentially overlooking relevant findings from non-English-speaking contexts. Second, the decision to include only quantitative studies systematically excludes research adopting qualitative methodologies. Future systematic reviews could address this gap by incorporating qualitative literature, thereby complementing the insights derived from quantitative studies with a more nuanced understanding of the subjective, emotional, and social dimensions of OHS. Third, all included studies were conducted in Europe and North America, suggesting a potential geographic bias in existing literature. As a result, current conceptualizations and operationalizations of OHS may be shaped by a Western-centric perspective, potentially overlooking important regional and cultural variations in how OHS is expressed and experienced by SGM individuals in other global contexts. Fourth, most of the reviewed studies on OHS have treated the SGM targets as a monolithic group or have focused broadly on sexual minorities, often without distinguishing between the specific identities within this umbrella category. As a result, OHS targeting different SGM subgroups, such as bisexual, pansexual, transgender, non-binary, and genderqueer people, remains largely unexamined. This homogenization risks obscuring the unique forms of OHS that may target specific identities and the different psychological, social, and contextual impacts they may entail. Fifth, the studies use diverse methodologies ranging from quantitative to mixed methods. This diversity may enrich the understanding of OHS, but it also reflects a fragmentation of knowledge on this topic. This fragmentation is also reflected by the terminological heterogeneity. Definitions vary widely, from “online hate speech” to “digital microaggressions,” and “targeted gender and sexuality-based violence.” There is an important need to establish conceptual consensus on OHS targeting SGM to improve methodological rigor in this line of research. Sixth, the review highlights that research on the perpetration of OHS toward SGMs remains relatively limited. Further studies could usefully address this dimension by offering empirical insights into the motivations associated with SGMs’ OHS perpetration, its impacts, and other factors related to the offenders. Finally, OHS experiences among SGM people facing multiple, overlapping forms of marginalization (e.g., SGM status in combination with race/ethnicity) remain underexamined. Future research should explicitly incorporate intersectional designs and measures to better capture heterogeneity in exposure and consequences and to inform more targeted prevention and support.

Implications

Despite limitations, this review offers important directions for future research. First, OHS targeting SGMs should be studied within broader models of online anti-SGM harassment to identify both shared and unique drivers of different forms of cyber violence, advancing conceptual clarity and methodological rigor. Second, research must account for the diversity of sexual and gender identities. For example, while transphobic OHS showed no direct link to attitudes toward transgender people unless moderated by politics (Schäfer et al., 2024), homophobic OHS was tied to reduced social cohesion (Schäfer et al., 2022). Such differences highlight the need to disaggregate SGM groups, especially given the prominence of trans rights debates and distinct forms of aggression like misgendering. Third, longitudinal studies are needed to examine the long-term mental health and social impacts of OHS on both SGM and non-SGM populations. Finally, more research is needed with youth, since developmental stages may shape both the processes and impacts of OHS. Early adolescence, in particular, is a key period of identity formation, where online hostility may produce differentiated and long-lasting effects.

The review also underscores practice and policy implications. Because OHS is consistently associated with poorer adjustment among SGM people, stronger, context-aware moderation policies combining artificial intelligence and human oversight are necessary (Arcila-Calderón et al., 2021; Burnap & Williams, 2016). Collaboration with SGM mental health experts could refine reporting systems, while schools, workplaces, and communities should adopt training and awareness programs to counter the normalization of OHS. Policymakers should develop bystander intervention policies that acknowledge potential risks. In fact, this review showed that intervening can sometimes harm bystanders or escalate OHS. Such policies must empower safe, effective responses, supported by evidence-based digital training on when and how to act, whether reporting hate speech, supporting targets, or posting counter-speech. Platforms can further encourage intervention through accessible reporting tools, automated prompts, and visibility for positive counter-speech, with policymakers incentivizing or mandating these features via accountability regulations. Public awareness campaigns can help normalize intervention, emphasize shared responsibility, and foster a more supportive online culture. Finally, OHS should be recognized as a form of minority stress in health care. Screening for online hate in mental health assessments, developing clinical guidelines, and funding SGM-specific services would help limit its impact.

Conclusion

Given the rapid intensification of OHS in recent years and the increasing number of adolescents exposed to harmful online content on a daily basis (Wachs et al., 2022), there is an urgent need for further research to deepen our understanding of the complexities of OHS. Such research is essential to informing effective strategies for prevention, support, and advocacy, particularly for SGM people, who are especially vulnerable to being targeted.

This review examines the main predictors associated with OHS targeting SGM people and underscores its impact at both individual and societal levels. At the personal level, exposure to OHS is associated with high risk for anxiety, depression, and perceived identity threat. On a broader societal level, it reduces social cohesion and increases social distancing, thereby reinforcing the marginalization of SGM communities. Reactions to OHS often arise when incivility is perceived and a sense of moral responsibility is triggered. While counter-speech can play a role in challenging OHS, its effectiveness in reshaping negative representations of SGM groups appears limited. By synthesizing existing literature with empirical data, this review aims to provide a systematic overview of key findings and methodological approaches developed to date. Furthermore, leveraging these insights is critical not only for identifying the specific characteristics of OHS but also for informing the development of effective policy strategies to limit this growing phenomenon.

Critical Findings

1. A total of 13 studies on OHS against SGM have been analyzed, indicating that research in this area is still in its early stages.
2. Most studies on OHS have focused predominantly on OHS targeting gay and lesbian groups, leaving OHS against other SGM identities relatively underexplored.
3. There is no clear definition of OHS against SGM, and no standardized measurement tools are used. In research, it should be recognized as distinct from overlapping forms of online violence involving individualized targeting, power dynamics, and repeated victimization, such as cyberbullying.
4. OHS exposure among SGM youth is alarmingly high, especially for SGM adolescents and young adults. It often targets both victims and allies.
5. OHS risk increases with higher visibility, multiple marginalized identities, acts of resistance or solidarity, and is shaped by platform moderation, sociopolitical context, and individual awareness.
6. Exposure to OHS against SGM has significant negative effects on both personal well-being and societal dynamics. It is linked to minority stress, poor mental health, and social withdrawal among SGM individuals. Limited evidence suggests it may also reduce social cohesion and increase polarization among non-SGM populations.
7. OHS against SGMs is generally seen as morally unacceptable, though perceptions vary with personal attitudes and moral reasoning. Lower acceptability is linked to greater bystander responsibility and willingness to intervene.

Summary of Implications
Research	OHS targeting SGMs needs to be included into broader models of anti-SGM cyberbullying and victimization in order to identify both commonalities and specificities across different forms of cyber violence, uncover shared social drivers, and promote greater conceptual clarity and methodological rigor in research. Research on OHS against SGMs should account for the complexity of diverse gender and sexual identities to better understand how these dynamics affect different groups and how intersecting identities shape experiences of OHS. The need for longitudinal studies to clarify the long-term mental health, social, and developmental impacts of OHS, particularly by comparing outcomes between SGM and non-SGM people. More research is needed with children and adolescents, as OHS during critical stages of identity development may have distinct and lasting consequences.
Practice	Given the link between OHS and the well-being of SGMs, stronger and more context-sensitive moderation policies are needed, with input from mental health experts and improved detection systems to effectively address harmful content. It is essential to creating awareness-raising initiatives for community members, such as teachers, students, government workers, and local initiative leaders, to help them recognize, address, and educate others about OHS targeting SGMs. Healthcare professionals should treat OHS targeting SGMs as a form of minority stress, integrating it into mental health assessments through tailored guidelines and intake questions that address online experiences.
Policy	Policymakers should advance safe and effective bystander intervention strategies to address OHS, through evidence-based training, platform features that support intervention, and public campaigns that promote active bystander engagement and a supportive online environment. Policymakers should allocate funding for mental health services tailored to SGM populations, particularly in areas with high levels of OHS, to ensure accessible and appropriate support.

Supplemental Material

sj-docx-1-tva-10.1177_15248380261429520 – Supplemental material for Understanding Online Hate Toward Sexual and Gender Minorities: A Systematic Review

Supplemental material, sj-docx-1-tva-10.1177_15248380261429520 for Understanding Online Hate Toward Sexual and Gender Minorities: A Systematic Review by Michela Mariotto, Sara Costa, Noemi Di Brango, Giuseppe Corbelli, Serena Verbena, Benedetta Emanuela Palladino, Antonio Zuffianò and Salvatore Ioverno in Trauma, Violence, & Abuse

Supplemental Material

sj-docx-2-tva-10.1177_15248380261429520 – Supplemental material for Understanding Online Hate Toward Sexual and Gender Minorities: A Systematic Review

Supplemental material, sj-docx-2-tva-10.1177_15248380261429520 for Understanding Online Hate Toward Sexual and Gender Minorities: A Systematic Review by Michela Mariotto, Sara Costa, Noemi Di Brango, Giuseppe Corbelli, Serena Verbena, Benedetta Emanuela Palladino, Antonio Zuffianò and Salvatore Ioverno in Trauma, Violence, & Abuse

Footnotes

ORCID iDs

Michela Mariotto

Sara Costa

Giuseppe Corbelli

Benedetta Emanuela Palladino

Antonio Zuffianò

Salvatore Ioverno

Ethical Considerations

This study is a systematic review of previously published literature. No new data were collected from human participants, and no identifiable personal data were used. Therefore, ethics approval was not required.

Consent to participate

Not applicable. No human participants were directly involved in this study.

Funding

The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This systematic review was funded by PRIN 2022 PNRR P2022BKBCA “Let’s Speak Up! Understanding the Impact of Online-Hate Speech on Adolescents’ daily life (SU! Project)” Funded by European Union—Next Generation EU, Mission 4 Componente 1, CUP: B53D23029810001.

Declaration of Conflicting Interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Data Availability Statement

This study is a systematic review. All the data were obtained from publicly available literature as cited in the manuscript. No new datasets were created or analyzed.

Supplemental Material

Supplemental material for this article is available online.

Author Biographies

Michela Mariotto, PhD, is a research fellow at the Department of Education, Roma Tre University. Her research primarily focuses on gender diversity in childhood and adolescence, with particular attention to the social conditions that shape embodiment, subjectivity, emotions, and systemic gender-based violence. Over the past decade, her work has centered on the experiences of gender-diverse children and their families, exploring the discursive and practical strategies they employ to navigate and make sense of these experiences. Adopting an interdisciplinary approach that integrates gender studies, sociology, anthropology, and social psychology, her research examines how gender categories are negotiated, contested, and reproduced within family and social contexts. From this perspective, she highlights the power dynamics that sustain structural inequalities and discrimination, while also shedding light on possible forms of resistance and social transformation.

Sara Costa, PhD, is a postdoctoral researcher at Roma Tre University. Her research focuses on social and clinical psychology, examining individual and contextual factors that shape well-being in school environments, with particular attention to students from minority backgrounds, including ethnic and LGBTQI+ communities.

Giuseppe Corbelli, PhD, is a postdoctoral researcher at Sapienza University of Rome and collaborates with Uninettuno University on multiple research initiatives and research projects. His research primarily focuses on the application of quantitative methods to the investigation of psychological processes and individual differences, with particular attention to constructs related to social cognitive theory and moral self-regulation. He is especially interested in understanding the cognitive and personality factors underlying prosocial and harmful behavior, as well as the determinants and effects of exposure to manipulated information on cognition and behavior. He holds an MS in Cognitive Processes and Technologies, and a PhD in Psychology (Mind and Technologies in the Digital Society) from Uninettuno University.

Noemi Di Brango, MA, is a first-year PhD student in Psychology and Social Neuroscience at Sapienza University of Rome, specializing in Personality and Organizational Psychology. After earning a master’s degree in Work and Organizational Psychology, she was awarded a research fellowship at the Department of Psychology at Sapienza University, where she contributed to the NextGenerationEU-funded PRIN PNRR 2022 project “Let’s Speak Up! Understanding the Impact of Online Hate Speech on Adolescents’ Daily Life.” In this project, she focused on the role of bystanders and the speaking up actions taken to counteract online hate speech.

Her current doctoral research explores the concept of meaning in life in adolescents and young adults, aiming to investigate the psychological and social factors contributing to the development of a sense of personal meaning during these key life stages.

Her research interests include positive psychology, psychological well-being, and the psychosocial dynamics in digital and educational contexts.

Serena Verbena, PhD, is a research fellow at the University of Florence. Her work focuses on developmental and social psychology, with particular attention to cultural diversity, social identity, and discrimination. She investigates how cultural and contextual factors influence individuals’ attitudes, emotions, and behaviors, with a special focus on ethnic microaggressions in educational settings and online hate speech targeting minority groups. Her research seeks to promote inclusion, equity, and intercultural understanding across both offline and online contexts.

Benedetta Emanuela Palladino, PhD, is an associate professor of Developmental and Educational Psychology at the University of Florence, Italy. Her research investigates bullying and cyberbullying as complex social experiences with deep emotional and developmental consequences, using longitudinal, cross-cultural, and intervention-based methodologies. More recently, she has focused on how bias-based and ethnic aggression shape developmental trajectories of emotional adjustment, empathy, and moral functioning. She explores how young people understand, narrate, and cope with peer victimization, discrimination, and online hate, paying particular attention to the psychological mechanisms that foster or hinder resilience and inclusion. She also examines how family attitudes, peer norms, and teacher support can amplify risk or promote well-being among youth exposed to prejudice and social exclusion. Deeply committed to translational research, she connects empirical evidence with school-based practices that cultivate empathy, justice, and safety for all students. She has participated in numerous national and European research projects focused on social inclusion, digital citizenship, and the prevention of youth violence. Through her work, she aims to bridge developmental science and applied practice to create environments where diversity and emotional well-being are actively valued and protected.

Antonio Zuffianò, PhD, is an associate professor of General Psychology at Sapienza, University of Rome. His research area of expertise concerns prosocial behavior, empathy-related responding, and psychological well-being in everyday life.

Salvatore Ioverno, PhD, is an associate professor of Clinical Psychology at the Department of Education, Roma Tre University. His research focuses on identifying risk and protective factors that influence minority stress, mental health, and academic success among LGBTQ+ individuals within educational settings. He employs cross-national and cross-cultural methodologies to investigate how institutional, interpersonal, and individual-level factors shape the well-being and development of SGM youth across diverse contexts. Professor Ioverno’s work contributes to a deeper understanding of the psychological and educational experiences of LGBTQ+ individuals, intending to inform inclusive educational policies and practices. His current research projects are dedicated to (a) investigating factors that affect the mental health and academic outcomes of LGBTQI+ university students; (b) exploring predictors of bystander intervention in response to online hate speech targeting LGBTQI+ individuals; and (c) examining the role of theory of mind in shaping children’s responses to discriminatory bullying. He has published widely on these topics in several peer-reviewed journals. Recent studies have addressed the impact of inclusive school policies on LGBTI youth across Europe, bystander behavior in school-based discrimination, and identity-related resilience factors among LGBTQ+ populations in different cultural contexts. Professor Ioverno also collaborates with international research networks to promote evidence-based interventions and policy reforms that support the mental health and educational equity of LGBTQ+ students.

References

Arcila-Calderón

Amores

J. J.

Sánchez-Holgado

Blanco-Herrero

(2021). Using shallow and deep learning to automatically detect hate motivated by gender and sexual orientation on Twitter in Spanish. Multimodal Technologies and Interaction, 5(10), 63–76. https://doi.org/10.3390/mti5100063

Baider

Anaxagorou

(2022). Evaluating hate speech: A sociolinguistic and bio signal experiment. Studii de lingvistică, 12(2), 263–296

Bartlett

Krasodomski-Jones

(2015). Counter-speech: Examining content that challenges extremism online. Demos. https://www.demos.co.uk/wp-content/uploads/2015/10/Counter-speech.pdf

Bedrosova

M. J.

Machackova

Šerek

Smahel

Blaya

(2022). The relation between the cyberhate and cyberbullying experiences of adolescents in the Czech Republic, Poland, and Slovakia. Computers in Human Behavior, 126, 107013 https://doi.org/10.1016/j.chb.2021.107013.

Bedrosova

M. J.

Dufkova

Machackova

Huang

Blaya

(2024). Bias-based cyberaggression related to origin, religion, sexual orientation, gender, and weight: Systematic review of young people’s experiences, risk and protective factors, and the consequences. Trauma, Violence, & Abuse, 26(1), 86–102. https://doi.org/10.1177/15248380241275971

Berger

M. N.

Taba

Marino

J. L.

Lim

M. S. C.

Skinner

S. R.

(2022). Social media use and health and well-being of lesbian, gay, bisexual, transgender, and queer youth: Systematic review. Journal of Medical Internet Research, 24(9), e38449. https://doi.org/10.2196/38449

Berrone

(2015). Cyberbullismo, disimpegno morale ed atmosfera morale percepita della scuola [Doctoral dissertation]. https://doi.org/10.13140/RG.2.1.1550.4084

Bilewicz

Soral

(2020). Hate speech epidemic. The dynamic effects of derogatory language on intergroup relations and political radicalization. Political Psychology, 41(S1), 3–33. https://doi.org/10.1111/pops.12670

Bishop

M. D.

Ioverno

Russell

S. T.

(2023). Sexual minority youth’s mental health and substance use: The roles of victimization, cybervictimization, and non-parental adult support. Current Psychology (New Brunswick, N.J.), 42(6), 5075–5087. https://doi.org/10.1007/s12144-021-01812-6

10.

Bishop

M. D.

Fish

J. N.

Russell

S. T.

(2024). The developmental collision hypothesis: An empirical test with three generations of sexual minority youth. Journal of Youth and Adolescence, 54(3), 559–573. https://doi.org/10.1007/s10964-024-02075-7

11.

Blaya

Audrin

(2019). Toward an understanding of the characteristics of secondary school cyberhate perpetrators. Frontiers in Education, 4, Article 46. https://doi.org/10.3389/feduc.2019.00046

12.

Boeckmann

R. J.

Liew

(2002). Hate speech: Asian American students’ justice judgments and psychological responses. Journal of Social Issues, 58(2), 363–381. https://doi.org/10.1111/1540-4560.00265

13.

Brown

(2017). What is hate speech? Part 1: The myth of hate. Law and Philosophy, 36(4), 419–468. https://doi.org/10.1007/s10982-017-9297-1

14.

Brown

(2018). What is so special about online (as compared to offline) hate speech? Ethnicities, 18(3), 297–326. https://doi.org/10.1177/1468796817709846

15.

Burnap

Williams

M. L.

(2016). Us and them: Identifying cyber hate on Twitter across multiple protected characteristics. EPJ Data Science, 5(11), 1–15. https://doi.org/10.1140/epjds/s13688-016-0072-6

16.

Carson

Knopf

Crawford

C. A.

Zapolski

T. C.

(2024). On the relationship between online heterosexist discrimination and mental health and substance use among LGBTQ+ young adults. Archives of Sexual Behavior, 53(5), 1277–1291. https://doi.org/10.1007/s10508-023-02800-6

17.

Cervone

Augoustinos

Maass

(2021). The language of derogation and hate: Functions, consequences, and reappropriation. Journal of Language and Social Psychology, 40(1), 80–101. https://doi.org/10.1177/ 0261927X20967394

18.

Citron

D. K.

(2014) Hate Crimes in Cyberspace. Harvard University Press

19.

Cohen-Almagor

(2015). Confronting the Internet’s Dark Side: Moral and Social Responsibility on the Free Highway. Cambridge University Press.

20.

Costello

Rukus

Hawdon

(2019). We don’t like your type around here: Regional and residential differences in exposure to online hate material targeting sexuality. Deviant Behavior, 40(3), 385–401. https://doi.org/10.1080/01639625.2018.1426266.

21.

Delgado

Stefancic

(2019). Understanding words that wound. Routledge. https://doi.org/10.4324/9780429503351

22.

Dreißigacker

Müller

Isenhardt

Schemmel

(2024). Online hate speech victimization: consequences for victims’ feelings of insecurity. Crime Science, 13(4), 1–13. https://doi.org/10.1186/s40163-024-00204-y

23.

Fish

J. N.

Bishop

M. D.

Russell

S. T.

(2023). Age trends in bias-based bullying and mental health by sexual orientation and gender identity. Prevention science, 24(6), 1142–1151, https://doi.org/10.1007/s11121-023-01530-4

24.

Fisher

C. B.

Tao

Ford

(2024). Social media: A double-edged sword for LGBTQ+ youth, Computers in Human Behavior, 156, 108194. https://doi.org/10.1016/j.chb.2024.108194.

25.

Fulantelli

Taibi

Scifo

Schwarze

Eimler

S. C.

(2022). Cyberbullying and cyberhate as two interlinked instances of cyber-aggression in adolescence: A systematic review. Frontiers in Psychology, 13, 909299. https://doi.org/10.3389/fpsyg.2022.909299

26.

Gámez-Guadix

Íncera

(2021). Homophobia is online: Sexual victimization and risks on the internet and mental health among bisexual, homosexual, pansexual, asexual, and queer adolescents. Computers in Human Behavior, 119, Article 106728. https://doi.org/10.1016/j.chb.2021.106728

27.

Gámez-Guadix

Mateos-Pérez

Wachs

Wright

Martínez

Íncera

(2022). Assessing image-based sexual abuse: Measurement, prevalence, and temporal stability of sextortion and nonconsensual sexting (“revenge porn”) among adolescents. Journal of Adolescence, 94(5), 789–799. https://doi.org/10.1002/jad.12064

28.

Gámez-Guadix

Sorrel

M. A.

Martínez-Bacaicoa

(2023). Technology-facilitated sexual violence perpetration and victimization among adolescents: A network analysis. Sexuality Research and Social Policy, 20(3), 1000–1012. https://doi.org/10.1007/s13178-022-00775-y

29.

Hatzenbuehler

M. L.

McLaughlin

K. A.

Keyes

K. M.

Hasin

D. S

. (2010). The impact of institutional discrimination on psychiatric disorders in lesbian, gay, and bisexual populations: A prospective study. American Journal of Public Health, 100(3), 452–459, https://doi.org/10.2105/AJPH.2009.168815

30.

Hawdon

Oksanen

Räsänen

(2017). Exposure to online hate in four nations: A cross-national consideration. Deviant Behavior, 38(3), 254–266. https://doi.org/10.1080/01639625.2016.1196985

31.

Hilte

Markov

Ljubešić

Fišer

Daelemans

(2023). Who are the haters? A corpus-based demographic analysis of authors of hate speech. Frontiers in Artificial Intelligence, 6, 986890. https://doi.org/10.3389/frai.2023.986890

32.

Ieracitano

Balenzano

Girardi

Gemmano

C. G.

Comunello

(2024). Online hate speech as a moral issue: Exploring moral reasoning of young italian users on social network sites. Social Science Computer Review, 42(1), 25–47. https://doi.org/10.1177/08944393231161124

33.

Kansok-Dusche

Ballaschk

Krause

Zeißig

Seemann-Herz

Wachs

Bilz

(2023). A systematic review on hate speech among children and adolescents: Definitions, prevalence, and overlap with related phenomena. Trauma Violence Abuse, 24(4), 2598–2615. https://doi.org/10.1177/15248380221108070

34.

Katz-Wise

S. L.

Hyde

J. S.

(2012). Victimization experiences of lesbian, gay, and bisexual individuals: A meta-analysis. The Journal of Sex Research, 49(2–3), 142–167. https://doi.org/10.1080/00224499.2011.637247

35.

Keighley

(2022). Hate hurts: Exploring the impact of online hate on LGBTQ+ young people. Women & Criminal Justice, 32(1–2), 29–48. https://doi.org/10.1080/08974454.2021.1988034

36.

Keipi

Näsi

Oksanen

Räsänen

(2017). Online hate and harmful content: Cross-national perspectives. Routledge.

37.

Kenski

Coe

Rains

S. A.

(2020). Perceptions of uncivil discourse online: An examination of types and predictors. Communication Research, 47(6), 795–814. https://doi.org/10.1177/0093650217699933

38.

Keum

B. T.

Miller

M. J.

(2017). Racism in digital era: Development and initial validation of the Perceived Online Racism Scale (PORS v1.0). Journal of Counseling Psychology, 64(3), 310–324. https://doi.org/10.1037/cou0000205

39.

Kmet

Lee

R. C.

Cook

L. S.

(2004). Standard quality assessment criteria for evaluating primary research papers from a variety of fields (AHFMR HTA Initiative No. 13). Alberta Heritage Foundation for Medical Research. https://doi.org/10.7939/R37M04F16

40.

Kwan

Dickson

Richardson

MacDowall

Burchett

Stansfield

Brunton

Sutcliffe

Thomas

(2020). Cyberbullying and children and young people’s mental health: a systematic map of systematic reviews. Cyberpsychology, Behavior, and Social Networking, 23(2),72–82. https://doi.org/10.1089/cyber.2019.0370

41.

Latané

Darley

J. M.

(1970). The unresponsive bystander: Why doesn’t he help? Appleton-Century-Crofts.

42.

Leonhard

Rueß

Obermaier

Reinemann

(2018). Perceiving threat and feeling responsible: How severity of hate speech, number of bystanders, and prior reactions of others affect bystanders’ intention to counterargue against hate speech on Facebook. Studies in Communication and Media, 7(4), 555–579. https://doi.org/10.5771/2192-4007-2018-4-555

43.

MacAvaney

Yao

H.-R.

Yang

Russell

Goharian

Frieder

(2019). Hate speech detection: Challenges and solutions. PLOS ONE, 14(8), e0221152. https://doi.org/10.1371/journal.pone.0221152

44.

Mancini

Imperato

(2020). Can social networks make us more sensitive to social discrimination? E-contact, identity processes and perception of online sexual discrimination in a sample of Facebook users. Social Sciences, 9(4), 47. https://doi.org/10.3390/socsci9040047

45.

Marciano

Antebi-Gruszka

(2020). Offline and online discrimination and mental distress among lesbian, gay, and bisexual individuals: The moderating effect of LGBTQ facebook use. Media Psychology, 25(1), 27–50 https://doi.org/10.1080/15213269.2020.1850295

46.

Martínez-Bacaicoa

Alonso-Fernández

Wachs

(2023). Prevalence and motivations for technology-facilitated gender- and sexuality-based violence among adults: A mixed-methods study. Sex Roles, 89, 670–684. https://doi.org/10.1007/s11199-023-01412-7.

47.

McConnell

E. A.

Clifford

Korpak

A. K.

Phillips

Birkett

(2017). Identity, victimization, and support: Facebook experiences and mental health among LGBTQ youth. Computers in Human Behavior, 76, 237–244. https://doi.org/10.1016/j.chb.2017.07.026

48.

McHugh

M. L.

(2012). Interrater reliability: The kappa statistic. Biochemia Medica, 22(3), 276–282. https://doi.org/10.11613/BM.2012.031

49.

McInroy

L. B.

Beer

O. W.

Scheadler

T. R.

Craig

S. L.

Eaton

A. D.

(2024). Exploring the psychological and physiological impacts of digital microaggressions and hostile online climates on LGBTQ+ youth. Current Psychology, 43(3), 2586–2596. https://doi.org/10.1007/s12144-023-04435-1

50.

Meyer

I. H.

(2003). Prejudice, social stress, and mental health in lesbian, gay, and bisexual populations: Conceptual issues and research evidence. Psychological Bulletin, 129(5), 674–697. http://dx.doi.org/10.1037/0033-2909.129.5.674

51.

Mulvey

K. L.

Hoffman

A. J.

Gönültaş

Hope

E. C.

Cooper

S. M.

(2018). Understanding experiences with bullying and bias-based bullying: What matters and for whom? Psychology of Violence, 8(6), 702–711. https://doi.org/10.1037/vio0000206

52.

Obermaier

Schmid

U. K.

Rieger

(2023). Too civil to care? How online hate speech against different social groups affects bystander intervention. European Journal of Criminology, 20(3), 817–833. https://doi.org/10.1177/14773708231156328

53.

Obermaier

Schmuck

(2022). Youths as targets: Factors of online hate speech victimization among adolescents and young adults. Journal of Computer-Mediated Communication, 27(4), 1–11. https://doi.org/10.1093/jcmc/zmac012

54.

Ouzzani

Hammady

Fedorowicz

Elmagarmid

(2016). Rayyan—A web and mobile app for systematic reviews. Systematic Reviews, 5(210), 1–10. https://doi.org/10.1186/s13643-016-0384-4

55.

Paasch-Colberg

Strippel

Trebbe

Emmer

(2021). From insult to hate speech: Mapping offensive language in German user comments on immigration. Media and Communication, 9(1), 171–180. https://doi.org/10.17645/mac.v9i1.3399

56.

Page

M. J.

McKenzie

J. E.

Bossuyt

P. M.

Boutron

Hoffmann

T. C.

Mulrow

C. D.

Shamseer

Tetzlaff

J. M.

Akl

E. A.

Brennan

S. E.

Chou

Glanville

Grimshaw

J. M.

Hróbjartsson

Lalu

M. M.

Loder

E. W.

Mayo-Wilson

McDonald

. . . Moher

(2021). The PRISMA 2020 statement: an updated guideline for reporting systematic reviews (2021). British Medical Journal, 372(71), 1–9. https://doi.org/10.1136/bmj.n71

57.

Patchin

J. W.

Hinduja

(2010). Cyberbullying and self-esteem. The Journal of School Health, 80(12), 614–624. https://doi.org/10.1111/j.1746-1561.2010.00548.x

58.

Powell

Scott

A. J.

Henry

(2020). Digital harassment and abuse: Experiences of sexuality and gender minority adults. European Journal of Criminology, 17(2), 199–223. https://doi.org/10.1177/1477370818788006

59.

Rest

J. R.

Narvaez

Thoma

S. J.

Bebeau

M. J.

(1999). DIT2: Devising and testing a revised instrument of moral judgment. Journal of Educational Psychology, 91(4), 644–659. https://doi.org/10.1037/0022-0663.91.4.644

60.

Roberts

S. R.

Salk

R. H.

Thoma

B. C.

Romito

Levine

M. D.

Choukas-Bradley

(2021). Disparities in disordered eating between gender minority and cisgender adolescents. The International Journal of Eating Disorders, 54(7), 1135–1146. https://doi.org/10.1002/eat.2349

61.

Russell

S. T.

Sinclair

K. O.

Poteat

V. P.

Koenig

B. W.

(2012). Adolescent health and harassment based on discriminatory bias. American Journal of Public Health, 102(3), 493–495. https://doi.org/10.2105/AJPH.2011.300430

62.

Saha

Chandrasekharan

De Choudhury

(2019). Prevalence and psychological effects of hateful speech in online college communities. In Proceedings of the 10th ACM Conference on Web Science, (pp. 255–264). Association for Computing Machinery. https://doi.org/10.1145/3292522.3326032

63.

Schäfer

Rebasso

Boyer

M. M.

Planitzer

A. M.

(2024). Can we counteract hate? Effects of online hate speech and counter speech on the perception of social groups. Communication Research, 51(5), 553–579. https://doi.org/10.1177/00936502231201091

64.

Schäfer

Sülflow

Reiners

(2022). Hate speech as an indicator for the state of the society: Effects of hateful user comments on perceived social dynamics. Journal of Media Psychology: Theories, Methods, and Applications, 34(1), 3–15. https://doi.org/10.1027/1864-1105/a000294

65.

Tao

Fisher

(2023). Associations among web-based civic engagement and discrimination, web-based social support, and mental health and substance use risk among LGBT youth: Cross-sectional survey study. Journal of Medical Internet Research, 25, e46604. https://doi.org/10.2196/46604

66.

Tennakoon

(2021). Can the “Dark Triad” traits be a predictor of cyber hate speech? Academia Letters. Article 1965. https://doi.org/10.20935/AL1965

67.

Thoma

B. C.

Salk

R. H.

Choukas-Bradley

Goldstein

T. R.

Levine

M. D.

Marshal

M. P.

(2019). Suicidality disparities between transgender and cisgender adolescents. Pediatrics, 144(5), e20191183. https://doi.org/10.1542/peds.2019-1183

68.

Tokunaga

R. S.

(2010). Following you home from school: A critical review and synthesis of research on cyberbullying victimization. Computers in Human Behavior, 26(3), 277–287. https://doi.org/10.1016/j.chb.2009.11.014

69.

Tynes

B. M.

Rose

C. A.

Williams

D. R.

(2010). The development and validation of the online victimization scale for adolescents. Cyberpsychology: Journal of Psychosocial Research on Cyberspace, 4(2), 1–15.

70.

Van Houtven

Acquah

S. B.

Obermaier

Saleem

Schmuck

. (2024). “You got my back?” Severity and counter-speech in online hate speech toward minority groups. Media Psychology, 27(6), 923–954. https://doi.org/10.1080/15213269.2023.2298684

71.

Wachs

Gámez-Guadix

Wright

M. F.

(2022). Hate speech victimization and depressive symptoms among adolescents: The protective role of resilience. Cyberpsychology, Behavior, and Social Networking, 25(7), 416–423. https://doi.org/10.1089/cyber.2022.0009

72.

Wilson

Cariola

L. A.

(2020). LGTBIQ+ youth and mental health: A systematic review of qualitative research. Adolescent Research Review, 5, 187–211. https://doi.org/10.1007/s40894-019-00118-w

Supplementary Material

Please find the following supplemental material available below.

For Open Access articles published under a Creative Commons License, all supplemental material carries the same license as the article it is associated with.

For non-Open Access articles published, all supplemental material carries a non-exclusive license, and permission requests for re-use of supplemental material or any part of supplemental material shall be sent directly to the copyright owner as specified in the copyright notice associated with the article.

0.00 MB

4.13 MB

0.03 MB