Gendered Morality and Backlash Effects in Online Discussions: An Experimental Study on How Users Respond to Hate Speech Comments Against Women and Sexual Minorities

Analyzing the diffusion of feminist discourses on Chinese social media: A case study of the 2022 Tangshan restaurant attack

Network platforms have ushered in a novel propagation model for feminist discourses. The emergence of oriental feminism in society has led to gender-based public opinions surrounding public events becoming a trending topic on Chinese social media. This study uses the 2022 Tangshan restaurant attack as a case study, an incident that sparked widespread discussions across China in 2022. The research gathered 366,602 network communication nodes within a week and examined the communication networks of three types of content nodes (information, opinion, and appeasement) using the complex network modeling method. The findings revealed that all three types of information communication networks exhibit an apparent scale-free characteristic, and the "key minority" of nodes significantly affects information communication. Information-type and appeasement-type Weibo display notable similarities in the quantity and degree distribution of nodes within the communication networks and in the information decay rate. Moreover, authoritative information issuers have become the primary catalyst for information propagation. Conversely, opinion-type Weibo has the widest communication network diameter and features a high degree of participation, multilevel propagation, and a slow decay rate. This indicates that the interaction between opinion leaders and netizens has enhanced the depth and breadth of information diffusion for opinion-type Weibo.

Stereotypes and sexism? Effects of gender, topic, and user comments on journalists’ credibility

Gendered social roles raise assumptions about what female and male journalists ought to do. Prior studies have suggested that covering counter-stereotypical topics may decrease journalists’ source and their work’s message credibility. Pertaining also to prior studies on heuristic cues for credibility evaluation, user comments have been shown to serve as corrective, both positively and negatively affecting the perception of accompanying content. In an online survey with 417 German participants, we employed a 3 (author: female, male, and computer) × 2 (topic: stereotypically masculine and feminine) × 2 (comments: sexist and non-sexist) experimental design to investigate source and message credibility. Findings do not show differences in gender perception but between human authors (either female or male) and a computer (the control group). Covering counter-stereotypical topics indicates slightly less credibility for men and women if presented with non-sexist comments. In turn, sexist comments lead to slightly higher credibility, suggesting more elaborate engagement with sexism-affected content.

Moral Foundations, Himpathy, and Punishment Following Organizational Sexual Misconduct Allegations

We build on deontic justice and moral foundations theories to shed light on responses to sexual misconduct at work by proposing a model that explains why some third parties punish accusing victims and support alleged perpetrators. We theorize that when third parties are given conflicting he-said, she-said information, they intuitively evaluate organizational injustice based on moral values. We further theorize that binding moral foundations (loyalty, authority, purity) give rise to sympathy toward men accused of sexual misconduct and anger toward female accusers. Across five studies (total n = 5,413) utilizing archival, field, and vignette designs, we examined third-party responses to sexual misconduct accusations ranging in severity across several industries. Third-party endorsement of binding moral foundations was linked to increased perpetrator-directed sympathy and victim-directed anger (Studies 1–4). These emotions jointly mediated the relationship between binding values and credibility perceptions of the accusing victim and the alleged perpetrator (Studies 2 and 3). Moreover, victim credibility was negatively associated with social sanctions and punishment severity levied toward the accusing victim, and perpetrator credibility was negatively associated with the same punishment outcomes for the alleged perpetrator (Studies 3 and 4). In Study 5, we found that managers framing the accusing victim as disloyal exacerbated negative judgments and emotions toward the victim and positive judgments and emotions toward the perpetrator for individuals who highly ascribe to binding moral foundations. We discuss the theoretical contributions and practical implications of moral concerns on third parties’ emotions, judgments, and motivations to punish actors involved in sexual misconduct allegations.

Supplemental Material: The e-companion is available at https://doi.org/10.1287/orsc.2022.1652 .

Sexist Slurs: Reinforcing Feminine Stereotypes Online

Social media platforms are accused repeatedly of creating environments in which women are bullied and harassed. We argue that online aggression toward women aims to reinforce traditional feminine norms and stereotypes. In a mixed methods study, we find that this type of aggression on Twitter is common and extensive and that it can spread far beyond the original target. We locate over 2.9 million tweets in one week that contain instances of gendered insults (e.g., “bitch,” “cunt,” “slut,” or “whore”)—averaging 419,000 sexist slurs per day. The vast majority of these tweets are negative in sentiment. We analyze the social networks of the conversations that ensue in several cases and demonstrate how the use of “replies,” “retweets,” and “likes” can further victimize a target. Additionally, we develop a sentiment classifier that we use in a regression analysis to compare the negativity of sexist messages. We find that words in a message that reinforce feminine stereotypes inflate the negative sentiment of tweets to a significant and sizeable degree. These terms include those insulting someone’s appearance (e.g., “ugly”), intellect (e.g., “stupid”), sexual experience (e.g., “promiscuous”), mental stability (e.g., “crazy”), and age (“old”). Messages enforcing beauty norms tend to be particularly negative. In sum, hostile, sexist tweets are strategic in nature. They aim to promote traditional, cultural beliefs about femininity, such as beauty ideals, and they shame victims by accusing them of falling short of these standards.