#sendeanlat (#tellyourstory):Text Analyses of Tweets About Sexual Assault Experiences

On 11 February 2015, a 20-year-old university student, Ozgecan Aslan, was violently murdered in an attempted rape in Mersin, southern Turkey. This event led to a mass Twitter protest in the country. Women across the country started sharing the hashtag #sendeanlat (“#tellyourstory” in English). In the current exploratory study, 164,279 original tweets were analyzed using the text analytic approach called the Meaning Extraction Method. Results revealed the key themes of reactions to victim blaming, honor culture/namus, assault experiences, social media, and women’s responsibility. Policy, media, and mental-health-related implications and future research directions are discussed

Ingroup love, outgroup hate, and the gateway group effect: Comparing the direct and indirect impact of dual versus single identification

Decades of research in social identity have shown that people instinctively hold positive attitudes towards ingroup members and negative attitudes towards outgroup members. However, it remains unclear how people respond to individuals explicitly identified with both one’s ingroup and outgroup. We propose that when people are exposed to dual-identified individuals and groups (e.g., Muslim-Americans explicitly identifying with both their Muslim and American identities), intergroup attitudes will improve, driven more by the ingroup component (American), despite the presence of the outgroup component (Muslim). Moreover, we suggest exposure to dual-identification can also improve attitudes toward the broader outgroup (Muslims more generally), a phenomenon called the gateway-group effect. To test these hypotheses, we created a new measure of dual-identification and conducted three studies involving both Muslim-Americans and Mexican-Americans. Results confirmed that exposure to explicitly dual-identified groups improved attitudes towards the dual-identified group (e.g., Mexican-Americans) as well as toward the respective outgroup (e.g., Mexicans)