The Nature and Prevalence of Cyber-Aggression Targeting African-Americans on Twitter

Open Access
Lawson, Jordan Robert
Area of Honors:
Bachelor of Arts
Document Type:
Thesis Supervisors:
  • Diane Helen Felmlee, Thesis Supervisor
  • Stacy Silver, Honors Advisor
  • Cyber-Aggression
  • Cyber-Bullying
  • Twitter
  • African-Americans
  • Black-Americans
  • Social Media
  • Social Dominance Theory
  • Racism
  • Racial Stereotypes
  • Social Networks
  • Digital Networks
  • Social Network Analysis
This study investigates and analyzes racially-charged cyber-aggressive tweets targeting African-Americans on the social media platform, Twitter. Through a mixed-methods study using both content-analysis and quantitative methods, I collect and analyze publicly-available data from Twitter (tweets). First, I examine the accessibility of racially-aggressive tweets targeting African-Americans by searching for messages containing four distinct racially-charged terms (co*n, porch monkey, ni**er, stupid ni**er). Next, I investigate what common negative stereotypical themes are found in racially-aggressive tweets targeting African-Americans, and whether they align with traditional anti-black stereotypes. Additionally, the extent to which racially-aggressive tweets targeting African-Americans spread throughout social networks is considered. Finally, I examine whether there are patterns of defending victims of racist Twitter cyber-aggression, what those patterns may be, and the extent to which users intervene in it. To conduct the study, searches using an open-source, social media importing software are conducted using various terms typically employed to victimize African-Americans. A sample of these 6,437 tweets are then documented, interpreted, and contextualized to address the forthcoming research questions. Digital network visualizations are also included to demonstrate the ways in which these messages can spread throughout social networks. The results show that racist messaging online is indeed a persistent occurrence and is readily accessible to Twitter users. Furthermore, racist messages align with traditional stereotypical themes, and often result in a vicious cycle of online aggression among conversation participants.