The Influence of Sexism and Incivility in WhatsApp Political Discussions on Affective Polarization: Evidence from a 2022 Multi-Party Election in India

Abstract

In contemporary political discourse, the concern of affective polarization, often fueled by uncivil and sexist discourse, is notably evident in digital communication contexts like WhatsApp. In this study, we examined the potential effects of uncivil and sexist messages as well as moderator interventions against these messages coming from political in- and out-group members in such political groups through a survey experiment (N = 1,464) fielded during the 2022 Uttar Pradesh (India) Legislative Assembly Elections. We investigate these questions and extend the prior work on affective polarization by introducing a new measure of Average Inter-party Affective Distance, which provides a single metric to index overall polarization in a multi-party election context. Our results showed that exposure to sexist uncivil messages had no discernible effect on affective polarization, political participation, and voting intention. Additionally, moderator warnings against incivility had no significant effects. However, we observed a variation in how respondents processed these messages based on their preexisting attitudes; notably, individuals with less sexist views were more inclined to vote after being exposed to sexist uncivil messages. These findings suggest that the influence of incivility and sexism in messaging platforms like WhatsApp on the wider electorate’s political behavior and attitudes is relatively limited. This research contributes to our understanding of the role of digital political communication, highlighting the importance of message content and preexisting individual differences in shaping affective polarization and mobilization.

Keywords

affective polarization incivility sexism political campaigns WhatsApp

In the evolving landscape of contemporary political discourse, affective polarization, and interparty hostility have emerged as significant concerns (Iyengar et al. 2012, 2019). This trend is not only reshaping political interactions but also influencing individual political behaviors and attitudes. Simultaneously, the modern political landscape in democracies around the world has been undergoing a transformative shift, marked by an increasing participation of individuals from diverse racial, ethnic, and gender minority groups. This shift is evident in the changing composition of electoral candidates and those elected to office, reflecting a broader democratization of political representation (Hasan 2011; Jaffrelot and Kumar 2012; Krook and Nugent 2016; Kumar 2021; Schaeffer 2023). However, these positive developments often encounter reactionary responses, particularly in the form of racist and sexist backlashes in highly polarized segments of society (Algara and Hale 2019; Cassese and Barnes 2019).

This exploration into digital discourse and its implications is particularly relevant in the Indian context, where political and gender dynamics are rapidly evolving. Despite India’s notable progress in gender equality and increased women’s participation in the 2019 Lok Sabha Elections (Kumar 2021), the rise of women in politics has been met with increased misogynistic rhetoric. Instances like the derogatory remark made by Maharashtra state Bharatiya Janata Party (BJP) president Chandrakant Patil toward Nationalist Conference Party (NCP) MP Supriya Sule in May 2022, “Why are you (Sule) even in politics, just go home and cook,” (Press Trust of India 2022) exemplify the misogynistic norms prevalent in Indian political discourse. This setting provides a pertinent context for our study, as India is not only grappling with significant changes in gender dynamics but also witnessing the contentious interplay of sexist uncivil discourse in its evolving political landscape.

At the same time, as messaging applications like WhatsApp and Telegram become increasingly vital in modern campaign communications, particularly in the Global South, scholars express growing concern over instances of sexist incivility on these less regulated and closed platforms (Banaji et al. 2019). The veil of anonymity and end-to-end encryption unique to these platforms often emboldens online partisans, reducing inhibitions around engaging in sexist discourse within private messaging groups. Moreover, the lack of formal auditing mechanisms allows group members to remain largely unaccountable for their actions, fostering an environment conducive to democratically damaging discourse. The escalating intensity of political divisions and the role of online communication in exacerbating these divisions are key areas of concern (Nordbrandt 2023; Yarchi et al. 2021). In this context, sexist messages (particularly from out-group members) can fuel affective polarization and mobilize partisans, given their potential to evoke strong emotional responses and reinforce in-group/out-group distinctions (Ondercin and Lizotte 2021). Research has shown that digital platforms can amplify partisan sentiments, potentially leading to heightened polarization (Törnberg 2022).

However, alongside these growing incidences of sexist uncivil messages, there is evidence of such incivility being reported and criticized by good-faith supporters and group administrators (Bhandari et al. 2021). For instance, in the context of misinformation encounters, a notable behavior by group members is peer corrections, where individual members warn others who might have shared questionable content (Kalogeropoulos and Rossini 2023; Kuru et al. 2023). Similarly, in the context of political incivility, such corrections by peers or moderators of groups can serve as reconciliatory counter-messaging. In order to understand polarization dynamics in messaging applications, it is important to investigate both elements that can potentially polarize (sexist incivility) and counter-polarize (moderator intervention) individuals.

Furthermore, the way individuals react to these messaging threads can vary significantly, influenced by a range of key preexisting individual differences related to sexist incivility. For instance, the gender of the respondents could be a crucial moderating factor (see Ondercin and Lizotte 2021). Females, in particular, may respond more negatively to sexist messages that target women. Additionally, beliefs about gender roles or sexism might also play a significant role in determining how people perceive gender-based incivility (Banda and Cassese 2022).

The current study examines the effects of exposure to sexist uncivil messages and moderator interventions within political WhatsApp groups in India, studying the implications for affective polarization and mobilization against the backdrop of elections. There are several reasons why investigating the potential effects on the larger electorate may prove crucial. The first one is intermedia agenda setting and information flows: Research from misinformation shows that misleading content usually originates from more closed spaces like WhatsApp and eventually spreads to more open social media such as Twitter and Facebook (Javed et al. 2022). Collaborative closed spaces may eventually influence content through information operations (Starbird et al. 2019). News media also often report on social media and messaging applications or sources from these spaces (McGregor 2019). Hence, these messages gain larger audience while circulating across platforms. The second reason is the potential impact of the particular intensity and prominence of group members on such WhatsApp groups: Political messaging groups are usually composed of members highly interested and involved in politics (including campaigners, intelligence teams, beat reporters, and propagandists) where incivility may be either incidental or intentional (Dev 2018). Thus, the effects of content spilling out from these intense political discussion spaces to the wider public remains an important question to be investigated since these groups constitute a key digital space of campaign ground wars.

By conducting a preregistered online survey experiment during the weeks leading up to the 2022 Uttar Pradesh Legislative Assembly Elections, we sought to identify these mechanisms in a state with a population of around 200 million (roughly equal to the population of Brazil). This study offers a critical understanding of the interplay between digital communication, gender dynamics, affective polarization, and political mobilization in an electoral context outside of the Western context. It shows that sexist uncivil messages originating from WhatsApp political groups may not have the power to polarize or mobilize the larger electorate, although preexisting sexist beliefs of individuals seem to play a role in conditioning this mostly null effects.

Sexism-Fueled Incivility’s Effects on Affective Polarization and Mobilization

Prior research on incivility and sexism suggests that these concepts are closely related. Incivility has been defined as the “set of behaviors that threaten democracy, deny people their personal freedoms, and stereotype social groups” (Papacharissi 2004). Sexism reflects an antipathy toward women that has deep roots in fundamental biosocial conditions common across human groups (Glick and Fiske 1996). Indeed, incivility (violence) against women in politics has been regarded as a form of enforcement of existing patriarchal gender roles (Krook et al. 2016). Papacharissi (2004) developed a three-item index to evaluate the presence of incivility by assessing whether a discussant (1) threatens democracy, for example, by advocating the forceful overthrow of a democratic government, (2) uses stereotypes, ranging from mild labels like “liberal” to offensive slurs, and (3) infringes on others’ rights, including personal and free speech freedoms. This framework is particularly relevant when considering the nature of uncivil and sexist messaging. As identified by Samory et al. (2021), such messaging is characterized by “attacks, foul language, or derogatory depictions” aimed specifically at individuals because of their gender (p. 576).

This problem is further exacerbated in the online sphere, especially on closed-messaging applications, where anonymity and more intimate, closed environments potentially contribute to perpetuating harmful sexist stereotypes. The usage of such messaging applications has been observed to increase during periods of heightened political activity when political campaigns have been known to strategically deploy messaging groups for the purposes of coordination and communication (Dev 2018). Instead of facilitating deliberative and civic online political discourse, these chat groups are frequently inundated with uncivil behavior, which manifests itself in the form of sexist and racist messages, often from partisans who are deeply invested in political issues involving their preferred party (Yarchi et al 2021).

The severity of this issue is further underscored by a 2016 report from the Inter-Parliamentary Union (Inter-Parliamentary Union 2016), which focused on violence against women in politics. In this report, interviews with fifty-five female parliamentarians worldwide revealed a startling statistic: 41.8 percent of respondents had experienced sexist attacks through social media channels such as WhatsApp and Facebook. These attacks often involved the spread of sexist imagery or comments, highlighting the pervasive nature of this problem in digital communication spaces. While previous studies have demonstrated the effect of gender-based incivility on key political outcomes such as polarization and mobilization (Banda and Cassese 2022; Valentino et al. 2018), there is relatively little research exploring how such dynamics play out on closed-group messaging platforms.

Affective polarization, or interparty hostility, is defined as distrust and dislike between political groups (Druckman and Levendusky 2019). Unlike issue polarization, affective polarization is driven less by ideological positions and more by affective or emotional reactions and animosity (Iyengar et al. 2012, 2019). Some view affective polarization as a norm in political discussion, and partisans frequently resort to uncivil rhetoric to undermine their opponents (Gervais 2021). Incivility in discourse exacerbates affective polarization among partisans, and they are more likely to show anger when their partisan ingroup is under attack (Gervais 2021; Suhay et al. 2018). Uncivil online political discussions on political issues lead to polarization and sharpen perceived differences between opposing groups (Hwang et al. 2008; Neyazi et al. 2023). Gervais (2021) argues that uncivil rhetoric generates negative affective responses among opposing political entities as political incivility contradicts social norms. The use of uncivil rhetoric not only further antagonizes two partisan groups but, at the same time, decreases the chances for any deliberative consensus among such polarized groups (Hwang et al. 2008). Thus, taking into account in vs. out-party differences and the effects of sexism and incivility, we argue that incivility on messaging application chats will fuel polarization and mobilization:

H1. Exposure to uncivil sexist as compared to civil sexist messages from out-party source will increase affective polarization and intention for political participation for their respective party as well as vote intention.

Peer Interventions Against Sexism-Fueled Incivility

Not all members in a closed group are supportive of uncivil and sexist messages even when they originate from an in-party member; how such individuals react is determined to a large extent by the affordances of these platforms, such as the presence of moderator-based mechanisms (Bhandari et al. 2021). Misinformation research shows that peer corrections against harmful content, such as fake news in messaging applications like WhatsApp, are frequent (Ng and Neyazi 2022; Rossini et al. 2021). Given the prevalence of peer pushback or moderator interventions in online political discussions (Porten-Cheé et al. 2020), it is,therefore, crucial to understand whether and how these interventions could have an effect on those who get exposed to these disagreements. This is important because political reporters prefer to focus on disagreements and both sides of arguments (Matthes 2012) and bring attention to the fact that not all members of these groups are supportive of sexist or uncivil language.

In their investigation on the promise of comment moderation on mitigating the “nasty effect” plaguing online news articles about science and technology, Yeo et al. (2019) showed that the moderator interventions against uncivil comments reduced perceptions of bias toward these articles when compared to unmoderated conditions. The enforcement of comment moderation was believed to have improved the “brand” of the organization as readers’ perceived bias of online news decreased. When extended to the political domain, a scenario-based experiment in India showed that individuals expressed reduced support for their own party when they did not see any action by their party representatives against uncivil comments originating from co-partisans (Sharma et al. 2020). Hence, we propose that exposure to such interventions against uncivil messages might counteract the “nasty” effects:

H2. Moderator intervention against uncivil sexist messages for out-party will increase affective polarization and the intention for political participation for their own party.

Individual Differences: Gender and Sexism

We also examine the differences across genders and groups with varying levels of sexist views. That is, do men and women, or individuals with different sexist predispositions, differ in how they respond to sexist incivility in political discussion? One might expect that the presence of sexism in political messages coming from the supporters of any political party will drive away women from supporting such political parties. However, Cassese and Barnes (2019) found that the majority of white women persisted in their support for Donald Trump in the 2016 U.S. Presidential contest despite his ostensible sexist beliefs. In their discussion, Cassese and Barnes (2019) attributed this finding to how white women wish to maintain their privilege over other women. Glick and Fiske (1997) alluded to how both men and women can develop hostile sexist beliefs. For women who are hostile and sexist toward other women they “are likely to be traditionalists who also hold negative views of non-traditional women because such women (e.g., feminists, career women) threaten to do away with the gender-role distinctions that are integral to traditional women’s identities” (Glick and Fiske 1997: 130). Women’s self-perception varies because of the different experiences in their daily lives. Thus, as much as there are commonalities among people of the same sex, we cannot assume that women will respond the same way when they encounter sexism. Aside from inherent differences, women may display stronger effects in response to sexist incivility due to the complex interplay of their individual experiences, self-perceptions, and potentially conflicting desires to either challenge or maintain traditional gender roles and privileges.

H3. The effects of sexist incivility on affective polarization and mobilization will be stronger for female individuals.

Similar to the varied reactions observed across gender lines, the response to sexist uncivil messages is likely to also differ based on individuals’ levels of sexist attitudes. Valentino et al. (2018) highlight that individuals with lower levels of sexism may react more negatively to sexist messages, as their personal beliefs are in direct conflict with the sexist content (see also De Geus et al. 2022). This notion is supported by research from Swim et al. (1995), who found that individuals with egalitarian views are more likely to perceive and react strongly against sexism. Such individuals, being more attuned to gender equality, are likely to experience a heightened sense of injustice and moral outrage when encountering sexist content, leading to stronger emotional responses. Furthermore, research suggests that lower sexist beliefs are often associated with a higher awareness of gender discrimination, making these individuals more sensitive to sexist remarks (Becker and Swim 2011; Drury and Kaiser 2014; Gothreau et al. 2022). People with lower sexist views are expected to display stronger effects in response to sexist uncivil messages as their fundamental beliefs in equality and fairness are starkly contradicted, evoking a more intense reaction due to a greater perceived violation of these core values.

H4. The effects of sexist incivility on affective polarization and mobilization will be stronger for people with less sexist views.

The Empirical Context

The 2022 state assembly elections in Uttar Pradesh (UP), India’s most populous state with over 200 million population, saw women’s issues come to the forefront. With the state election initially set to be a two-way contest between the incumbent BJP and the regional party, Samajwadi Party (SP), the entry of the Indian National Congress (INC), a national party, with its focus on women voters, threatened the two-party hegemony (Sharma 2022). The INC’s women-centric campaign, led by Priyanka Gandhi Vadra, daughter of the former INC President Sonia Gandhi, sought to capitalize on the rising importance of the women’s vote, evidenced by substantial increases in female voter turnout observed not only nationally but also in the UP state level in recent years (Poojari 2022). Against this backdrop, the 2022 UP Assembly elections also witnessed a flurry of digital interactivity deployed by political parties, with WhatsApp being instrumental in campaign strategies. The IT cells (the political wings of parties that are in charge of digital campaigns) created thousands of WhatsApp groups to reach more than 100 million potential voters with targeted political messaging (Lakhwani 2022). However, WhatsApp has also become a potential tool for political parties to spread misinformation and exacerbate polarization (Campbell-Smith and Bradshaw 2019; Neyazi et al. 2021). While the UP elections witnessed the rise of WhatsApp messages as a prominent tactic in political canvassing, these messages were often rife with cross-party accusations; this was, again, a tactic deployed by partisans to mobilize voters (Pandey 2022).

Method

Recruitment

The study was preregistered in AsPredicted with an initial analysis outline (ID: 86707; refer to Supplemental Appendix 1). However, our final analysis departed from the initial framework due to the need for a narrower, more focused scope. Specifically, our paper focuses on studying the effects of exposure to sexist uncivil messages from out-party sources (H1) as well as peer verbal interventions (H2), along with considering potential moderating effects by gender and pre-existing sexism (H3 and H4).^1,2 Data collection took place from Feb. 2nd to Mar. 3rd, 2022, during the 2022 Uttar Pradesh Legislative Assembly Election.³ Participants in our study were eligible voters who had not yet cast their votes; we employed a screener to exclude any participants who had already voted. A total of 1,679 adult participants were recruited by YouGov, an established global survey agency. Our sample comprised an approximately equal number of males and females (female: 50.3%), who are mainly younger (18–29: 48.5%) and middle-aged (30–49: 46.2%) individuals. The majority fell within the lower-to-middle income bracket, earning between 10,000 INR and 100,000 INR per month (approximately $120 to $1,200 USD) (refer to Table A1 of Supplemental Appendix 2 for detailed statistics).

Procedures and Stimuli

Our study takes the form of a 3 (C1: less sexist uncivil, C2: more sexist uncivil without moderator, C3: more sexist uncivil with moderator) × 3 (BJP, INC, SP message source) between-subjects (one treatment per respondent) single-blind (respondent unaware of treatment assignment) design. Party identification (BJP, INC, SP supporter) and gender (male, female) were secondary variables used to cluster our respondents into more homogeneous groupings to improve power while maintaining generalizability. Participants were randomly assigned to the treatment groups with a male-female ratio of 1:1 and party identification (BJP, INC, SP) ratio of 1:1:1 in each group. The target quota for each combination of the two factors under each treatment group is 30. With six unique combinations and nine treatment groups, our target quota is thus 1,620. Random assignment was deemed to have been successful as no significant differences in the demographic composition of participants across the conditions were detected (see Supplemental Appendix 2).

Participants first answered pretreatment questions measuring their initial political behavior and level of sexism. Each respondent is then exposed to the stimuli in the form of a WhatsApp message screenshot displaying a conversation taking place between partisans on whether their party should award tickets to women candidates. The message contained sexist elements (see Supplemental Appendix 3) but differed in two key attributes: one, their justifications for excluding female candidates from the ballot, and two, in the party of the group. The civil (and control) condition argued that women candidates should be excluded based on a prior incident where a prominent woman politician was found to be involved in corruption, and members expressed agreement in a civilized manner. The uncivil condition argued that women belonged in the kitchen and that even if they were to be involved, they should be good-looking, with members expressing agreement uncivilly.⁴ The moderator aspect includes an intervention by a member criticizing the sexist and disrespectful nature of the conversation. The party affiliation of the group is identified in the first message, wherein the messenger indicates their party of choice and sets the tone of the conversation. The stimuli were administered for a minimum of thirty seconds, with respondents unable to move beyond the page before this time had elapsed. Immediately after reading the messages, participants answered a battery of survey questions measuring their post-treatment dispositions that included vote intention, political participation, and feelings toward political parties. At the end of the study, participants were briefed that the WhatsApp messages shown were not real but had been generated artificially for research purposes. They were further given the option to have their data deleted if they so chose. This study was approved by the National University of Singapore’s ethics committee.

Measures

Dependent Variables

Affective Polarization Toward Political Parties

The concept of affective polarization is primarily studied in relation to two-party systems (e.g., the United States). Extending this concept to multi-party contexts faces several challenges, given the complexity and strength of these feelings in environments where vote-switching is common, and voters often exhibit weaker partisan ties, sometimes showing loyalty and positive sentiments toward multiple parties at once (Garry 2007; Kekkonen and Ylä-Anttila 2021; Wagner 2021). Recent studies, however, have made progress on this front (Harteveld 2021; Gidron, et al. 2022; Wagner 2021). Building on this emerging line of research, we leverage existing measures of affective polarization from two-party systems (Druckman and Levendusky 2019; Iyengar et al. 2019) and extend them to multi-party contexts by defining a new metric termed as “average inter-party affective distance” (AIAD), which was operationalized as follows. Each respondent was asked to indicate on a feeling thermometer how they felt about each party (BJP, INC, SP); responses ranged from 0 to 100 with values above fifty indicating “warm” feelings, values below fifty indicating “cold” feelings and a value equal to fifty indicating a neutral affect. Detailed instructions were provided to facilitate understanding of what the slider scale represented. Given that this was a three-way contest, for each respondent, we were able to elicit one value for their in-party affect level (corresponding to the party they supported), and two values for their out-party affect level (corresponding to the remaining two parties). We then computed the absolute difference between the in-party affect and each of the two out-party affects, yielding two inter-party distances for each respondent. These two distances were then averaged to calculate the AIAD (M = 37.069, SD = 24.596),^5,6 which was used as a dependent variable. Higher AIAD for political parties thus reflected an increased out-party hostility toward one or more political parties, indicating heightened levels of affective polarization in the multi-party context.

Intention for Political Participation

To measure our respondents’ inclination to participate in politics, we asked: “How likely is it that you’ll participate in the following activities in the upcoming Uttar Pradesh assembly election?” The activities included: “I intend to discuss politics with my family and friends”, “I intend to take part in political demonstration” and “I intend to sign online petition”. Responses were measured on a five-point scale (1 = Not at all likely, 5 = Extremely likely) and combined to form an index of intention for political participation (M = 3.277, SD = 1.129, α= .798), which was used as a dependent variable.

Vote Intention

Our third dependent variable measured the likelihood of respondents to vote in the 2022 Uttar Pradesh Legislative Assembly Election. Respondents were asked on a five-point scale (1 = Very unlikely, 5 = Very likely): “How likely is it that you will vote in the upcoming Uttar Pradesh assembly election?” (M = 4.367, SD = 1.04).

Independent Variables (Manipulations)

Exposure to Uncivil Messages

The incivility of the WhatsApp messages, as shown in the treatment, was used to operationalize exposure to uncivil messages as a binary variable (with incivility coded as 1 and civility coded as 0).

Exposure to Moderator Intervention

The presence of an intervention by a moderator in the WhatsApp messages, as shown in the treatment, was used to operationalize exposure to moderator intervention as a binary variable (moderator intervention coded as 1 and no intervention coded as 0).

Moderators

Sexism

We adopted measures from the Ambivalent Sexism Inventory (Glick and Fiske, 1996) to measure hostility toward women. Five items were presented on a five-point scale (1 = strongly disagree; 5 = strongly agree): “Women seek to gain power by getting control over men”; “Women exaggerate problems they have at work”; “Once a woman gets a man to commit, she puts him on a tight leash”; “Women are too easily offended” and “Most women fail to appreciate fully all that men do for them.” Responses were combined to create an index of sexism (M = 3.276, SD = 1.032, α = .899).

Gender

We used the gender of the respondent as a moderator variable in our model with female coded as 1 and male as 0.

Manipulation Check

We excluded respondents who failed the manipulation check: 108 responded “No” or provided no response when asked if they were able to fully read the message and a further 107 indicated negatively when asked whether they read the moderator intervention. This left us with 1,464 respondents in total. Employing subjective manipulation checks, we observed that respondents assigned to the uncivil conditions tended to rate the stimuli as more uncivil than those in the civil condition with these differences being significant (see Supplemental Appendix 5). In addition, respondents across the three conditions (C1, C2, C3) tended to regard the language in the post as sexist. These findings thus provide evidence that the treatment was successful.⁷

Analytical Strategy

Central to our study is the polarizing and mobilizing effects stemming from exposure to sexist uncivil messages from out-party sources and whether peer verbal interventions are effective mitigators. We further determine if these effects depended on gender and pre-existing sexism. Evidence for these hypotheses was assessed using a hierarchical OLS regression procedure applied to relevant subsets of our data. First, we retain only those exposed to messages from out-party sources.⁸ This is achieved by first creating a composite variable as follows: (1) respondents who identified with the BJP (INC or SP) and saw a stimuli message from BJP (INC or SP) supporters were coded as exposed to an in-party message (coded =0, n = 485) and (2) those who identified with the BJP and saw a stimuli message from either INC or SP supporters were coded as exposed to an out-party message (other combinations were coded analogously) (coded = 1, n = 979). We then include only the latter subset who saw an out-party message. When assessing exposure to sexist uncivil messages, we further filter the data to only examine respondents who either saw the less or more sexist uncivil message without moderator intervention (C1 vs. C2; n = 704). On the other hand, when assessing the impact of peer interventions, we filter the data to examine only respondents who saw the more sexist uncivil message, both without and with moderator intervention (C2 vs. C3; n = 633).

Results

We present the results for the effect of exposure to sexist uncivil messages from out-party sources in Table 1. H1 suggests that this exposure will increase affective polarization and induce intention for political participation and voting. Focusing on the top panel of Table 1, we find insufficient evidence to establish significance of these effects on affective polarization (b = 2.669, p = .181), political participation (b = −.057, p = .456) and voting intention (b = .064, p = .396). Therefore, these results do not support H1, as no significant effects were observed from exposure to sexist uncivil messaging across the three dependent variables.

Table 1.

Effect of Exposure to Sexist Uncivil Messages from Out-Party Sources and Moderator Intervention.

	Average Inter-Party Affective Distance	Political Participation	Vote Intention
Intercept	53.845*** (3.752)	1.608*** (0.142)	3.785*** (0.138)
Exposure to sexist uncivil messages	2.669 (1.995)	−0.057 (0.077)	0.064 (0.075)
Female	−7.797*** (1.995)	0.296*** (0.077)	0.183* (0.075)
Sexism	−4.132*** (1.019)	0.481*** (0.039)	0.150*** (0.037)
N	623	681	676
R² (adjusted)	0.046	0.199	0.029
F	11.079***	57.289***	7.782***
Intercept	56.371*** (3.714)	1.722*** (0.147)	4.188*** (0.152)
Exposure to moderator intervention	−2.739 (2.007)	−0.064 (0.081)	−0.163⁺ (0.085)
Female	−8.187*** (1.998)	0.150⁺ (0.081)	0.042 (0.084)
Sexism	−4.030*** (0.999)	0.451*** (0.039)	0.068⁺ (0.041)
N	564	621	610
R² (adjusted)	0.052	0.176	0.006
F	11.213***	45.116***	2.313⁺

p < .1. *p < .05. **p < .01. ***p < .001.

Next, we examine the effect of peer verbal interventions, as detailed in the bottom panel of Table 1. H2 proposes that seeing a peer intervention will further affectively polarize respondents, in addition to increasing their political participation and voting intentions. However, similar to the previous findings, the estimated effects of peer intervention are not significant for affective polarization (b = −2.739, p = .173), political participation (b = −.064, p = .433), and vote intention (b = −0.163, p = .055). These findings contradict H2, indicating that the peer intervention did not have any observable impact on the dependent variables.

Turning now to the differential effects based on gender, H3 hypothesized that the (positive) effect of exposure to sexist uncivil messages (from out-party sources) would be stronger among women. The top panel of Table 2 presents estimates of these moderation effects for each dependent variable.⁹ However, the results show that gender does not significantly moderate the effects on affective polarization (b = −4.158, p = .298), political participation (b = −.100, p = .518) or voting intention (b = .001, p = .996). Consequently, these findings refute H3, as no significant gender-based moderating effects were found.

Table 2.

Moderating Effects of Gender and Sexism on Effect of Exposure to Sexist Uncivil Messages.

	Average Inter-Party Affective Distance	Political Participation	Vote Intention
Exposure to sexist uncivil messages × Female	−4.158 (3.991)	−0.100 (0.154)	0.001 (0.150)
N	623	681	676
Adjusted R²	0.046	0.198	0.028
F	8.582***	43.034***	5.828***
Exposure to sexist uncivil messages × Sexism	−2.213 (2.039)	−0.041 (0.077)	−0.203** (0.074)
N	623	681	676
Adjusted R² (adjusted)	0.047	0.198	0.038
F	8.607***	42.992***	7.757***

p < .1. *p < .05. **p < .01. ***p < .001.

Lastly, we examine the moderating effects of pre-existing sexism. H4 posits that the (positive) effect of exposure to sexist uncivil messages (from out-party sources) is stronger among those with less sexist predispositions. The bottom panel of Table 2 presents our findings. Notably, pre-existing sexism exhibits a negative moderating effect on voting intention: the conditional effect of exposure to sexist uncivil out-party messages on voting intention decreases by .203 (p = .006) for each unit increase in pre-existing sexism. This interaction is depicted in Figure 1, illustrating that respondents with lower levels of pre-existing sexism, upon encountering a sexist uncivil message from out-party sources, reported a higher intention to vote compared to those who encountered a less sexist message. On the other hand, no significant moderation effects could be found on either affective polarization (b = −2.213, p = .278) or political participation (b = −.041, p = .595). In sum, these results partially support H4: while individuals with lower sexism levels were more likely to vote following exposure to the sexist uncivil message, similar significant moderating effects were not evident for the other dependent variables.¹⁰

Discussion

This study analyzed the impact of exposure to (un)civil sexist messages shared in WhatsApp political groups by out-party supporters in polarizing and mobilizing potential voters if such influences are moderated by gender and sexism, and whether they could be mitigated through peer verbal interventions.¹¹ Our findings largely reveal null results, showing no significant evidence of polarizing or mobilizing effects from exposure to sexist uncivil messages from out-party sources. Similarly, no significant moderation effects in relation to gender were observed, which supports the existing findings by De Geus et al. (2022). However, we did find that exposure to sexist uncivil messages from out-party sources increases voting intention among respondents with lower preexisting sexism, although this effect was not observed for either affective polarization or political participation.¹² This is an important finding exhibiting respondents with lower levels of tolerance for sexism are more susceptible to mobilization in environments rife with sexist uncivil discourse. While the rejection of gender discrimination is a positive societal trait, our study reveals that it could paradoxically lead to increased discord within society, particularly in the context of sexist and uncivil conversations initiated by supporters of out-parties.

The finding that exposure to sexist uncivil conversations does not, on average, increase polarization or induce mobilization among women is interesting, as it suggests that the effect of incivility above and beyond sexism doesn’t polarize or mobilize women further. That is, when exposed to sexist elements in online closed-group conversations, any supplementary impact from an additional uncivil element is negligible. This can perhaps be explained by alluding to a “drowning-out” phenomenon (Erzikova and McLean 2020) for females, where the effects of cursory incivility are overshadowed by those arising from deep-seated prejudices such as sexism. Indeed, female participants, on average, found the WhatsApp stimuli messages to be more sexist than their male counterparts. In contrast, from the perspective of incivility, they regard themselves as being less uncivil as compared to male participants (see Supplemental Appendix 14). These differential ratings of sexism and incivility accorded by female participants in our study corroborate our “drowning-out” hypothesis, though further research is required for establishing more concrete evidence. Contrary to prior research that distinguishes between different types of sexism (Glick and Fiske 1997; Sharifirad and Matwin 2019), our findings suggest that for women, the nature of sexism (whether hostile or benevolent, less or more uncivil) is inconsequential. This challenges existing literature and aligns with the argument by Samory et al. (2021) that sexist messages should be condemned purely based on their content.

Despite several null findings, the strength of our experimental design, coupled with rigorous power analysis and successful treatment checks, leads us to posit that our results reflect the inefficacy of sexist uncivil discourse in generating a polarizing and mobilizing response in the real world. This is in line with recent literature: Reich and Bachl (2023), for instance, showed that sexist incivility manifesting in online discussions bears no discernible effect on one’s tendency to take part in the discussion. Furthermore, a comprehensive meta-analysis into the relationship between political incivility and political mobilization by Van’t Riet and Stekelenburg (2022) found that political incivility had little-to-no effect on political participation, despite evidence alluding to geography-based differences. Similarly, Neyazi et al. (2023) show that incivility in the context of online political campaigns has limited impact on voter mobilization and affective polarization.

In contemporary politics, disproportionate levels of incivility toward female politicians, especially those who receive higher levels of public attention, have unfortunately been common (Rheault et al. 2019). Sexist behavior toward women in politics has, in fact, been regarded “as a form of gender role enforcement” (Krook and Restrepo 2016: 466), with women in electoral politics perceived as a challenge to existing gender norms, which in turn facilitates sexist behaviors against women (Beauregard and Sheppard 2021). Furthermore, these gender-based prejudices are not without important implications on key political outcomes, with considerable evidence showing racial attitudes and sexism shaping voter decisions in the 2016 U.S. Presidential elections (Algara and Hale 2019; Banda and Cassese 2022; Cassese and Barnes 2019).

Our results also suggest that peer interventions are not effective in addressing the polarizing and mobilizing effects of out-party sexist uncivil messages. This finding of a null effect could be due to our study employing a direct form of peer intervention (Kim 2021) in the sense that a group member replied to another peer criticizing their use of sexist uncivil comments in the conversation. The fact that such direct intervention is not found to have any effects on affective polarization, despite passing all manipulation checks, could be owing to differing possible perceptions of the moderator intervention from the perspective of the observer: in the eyes of some, it could be interpreted as a corrective action taken by an in-group peer against a fellow member for undesirable elements in the WhatsApp conversation whereas for others it may serve only to accentuate the norm-violating behavior embodied in the conversation. Hence, the implications of the moderator intervention are not immediately clear. Future studies seeking to establish the efficacy of in-group interventions should address such conflicting interpretations in their experimental design to mitigate such issues.

The larger focus of our study on WhatsApp has certain implications. Besides facilitating civic and political engagement (Moura and Michelson 2017), WhatsApp has been weaponized for political propaganda, as evidenced by the 2018 Brazilian elections (Magenta et al. 2018; Santini et al. 2021) and in misinformation campaigns in India (Campbell-Smith and Bradshaw 2019; Garimella and Eckles 2020; Neyazi et al. 2021; Vasudeva and Barkdull 2020). These campaigns often involve manipulated content, leading to polarization and violence. However, our findings, contrasting with this backdrop, show that most voters are not influenced by uncivil messages from the platform, with the notable exception of those with lower sexism levels, which exhibited higher voting intentions. This highlights the complexity and importance of analyzing messaging app content’s effects on diverse user groups.

Limitations and Future Research

In this section, we address several limitations of the current study. First, our study is based on an online experiment which might lack external validity: the design of the experimental interface (presenting the WhatsApp conversations as screenshots) and its administration through a web browser meant that our respondents might have behaved very differently than if they were actually on a closed messaging platform such as WhatsApp. Future research on this topic may explore alternative field experiment designs incorporating a custom messaging application developed for research. Second, the moderator intervention is only applied to more sexist uncivil messages (and not to less sexist uncivil messages), which makes it difficult to isolate the effect of the moderator intervention from that of the civility of the messages. Nevertheless, this limitation doesn’t affect our analysis since our focus is to look at the effect of the moderator intervention in uncivil settings, which has become a contentious issue in the current political discourse. Third, the presence of sexist language was included in all experimental conditions, albeit to varying degrees. This design effectively grounds our study of sexist incivility in contexts where sexism is already present and renders us unable to contrast against exposure to civil messages where sexist incivility is absent. While insightful for real-world contexts where sexism is prevalent, we do not discount the potential for additional insights; future studies could explore along these lines. Fourth, we used only a few custom-generated sexist uncivil messages as stimuli, which may not be representative of real-life sexist discussions transpiring on closed platforms such as WhatsApp.

Conclusion

Despite these limitations, our study makes two important contributions. First, we extend the concept of affective polarization to a multi-party system in the Global South. While previous studies have validated the use of feeling thermometers in multi-party contexts (Gidron et al. 2022), our research goes a step further by introducing a measure to capture the average inter-party affective distance.¹³ Hence, the study attempts to advance the literature on affective polarization beyond the customary bi-party system to also apply to multi-party systems. Second, our study sheds light on the differential effects of exposure to sexist uncivil conversations in closed groups on vote intention, showing that individuals with lower tolerance for sexism are more likely to be mobilized. Interestingly, in situations where sexist elements are already present in the discourse, the addition of mere incivility does not further polarize females, supporting the “drowning-out” effect. This suggests that deeply rooted prejudices like sexism can overshadow additional, more cursory elements of incivility in influencing female perspectives. In conclusion, this study not only broadens the understanding of affective polarization and political mobilization in multi-party systems but also provides critical insights into the gendered responses to sexism and incivility in political discourse within closed messaging environments, underscoring the complex interplay of these factors in shaping political attitudes and behaviors.

Supplemental Material

sj-pdf-1-hij-10.1177_19401612241242431 – Supplemental material for The Influence of Sexism and Incivility in WhatsApp Political Discussions on Affective Polarization: Evidence from a 2022 Multi-Party Election in India

Supplemental material, sj-pdf-1-hij-10.1177_19401612241242431 for The Influence of Sexism and Incivility in WhatsApp Political Discussions on Affective Polarization: Evidence from a 2022 Multi-Party Election in India by Taberez Ahmed Neyazi, Ozan Kuru and Subhayan Mukerjee in The International Journal of Press/Politics

Footnotes

Declaration of Conflicting Interests

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

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This research is supported by the Ministry of Education, Singapore, under the Academic Research Fund Tier1 (FY2020). This study is part of our Digital Campaigns and Propaganda Lab.

ORCID iD

Taberez Ahmed Neyazi

Supplemental Material

Supplemental material for this article is available online.

Notes

Author Biographies

Taberez Ahmed Neyazi is an Assistant Professor of Political Communication and New Media and a Principal Investigator at the Centre for Trusted Internet and Community at the National University of Singapore. His research interests include political communication and public opinion; computational social science; digital, mobile, and social media and communication theory. He is the author of Political Communication and Mobilization: The Hindi Media in India, Cambridge University Press, 2018, and has published several journal articles.

Ozan Kuru is an Assistant Professor of Digital Media at the Department of Communications and New Media and a Principal Investigator at the Centre for Trusted Internet and Community of the National University of Singapore. He is broadly interested in individuals’ interaction with systematic information about politics, health, and science as they are mediated and socially construed via institutional and social media platforms.

Subhayan Mukerjee is an Assistant Professor of Digital Media at the Department of Communications and New Media and a Principal Investigator at the Centre for Trusted Internet and Community of the National University of Singapore. Subhayan situates his research at the intersection of digital media and online human behavior, drawing from a wide repertoire of computational methods that blend observational as well as experimental approaches – such as network analysis, statistical inference, and agent-based simulations.

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