Cyber Aggression on Social Media: A Quasi-Experimental Study of Policy on Sexist and Racist Messages

• In Event: 3563 - Gender and Race in Media Production and Use

Abstract

Social media represents one of the newest forums for aggression, ones where hostility is experienced personally, and often contains sexist and racist content. It is commonplace to find abusive language directed toward women and racial or sexual minorities online. To stem some of the pervasive negativity, Twitter enacted a widely publicized policy to reduce abusive messaging. Here we examine the effect of this change on sexist and racist messages through a sentiment analysis of tweets. We analyze (over 3.6 million) messages containing the slur “bi!ch;” and additional messages with racist slurs. Adopting a quasi-experimental approach comparing tweets sent before and after this policy shift, we find evidence that the policy had a limited, but significant impact on user behavior. Tweets after the policy were more positive than before the change. In particular, the policy decreased the negative sentiment of messages containing sexist or racist content to some degree. The findings highlight the viciousness of negative messaging on Twitter as well as the potential for a positive influence of institutional policy. On a broad level, our findings call further attention to the serious, social problem inherent in cyberbullying within social media. It represents one of the first, large-scale studies in which negative Twitter messages are tracked that target individuals on the basis of gender and/or racial slurs. Of particular significance, our proposed research confirms, in an independent investigation, that certain organizational practices can successfully begin to limit the negativity of these increasingly common, problematic, online interactions.

Authors

• Diane H. Felmlee, Pennsylvania State University

• Daniel DellaPosta, Pennsylvania State University

• Paulina dela Cruz Inara Rodis

• Stephen A Matthews, Pennsylvania State University