IEEE VIS 2024 Content: Connections Beyond Data: Exploring Homophily With Visualizations

Connections Beyond Data: Exploring Homophily With Visualizations

Poorna Talkad Sukumar - New York University, Brooklyn, United States

Maurizio Porfiri - New York University, Brooklyn, United States

Oded Nov - New York University, New York, United States

Room: To Be Announced

2024-10-17T13:06:00Z GMT-0600 Change your timezone on the schedule page
2024-10-17T13:06:00Z
Abstract

Homophily refers to the tendency of individuals to associate with others who are similar to them in characteristics, such as, race, ethnicity, age, gender, or interests. In this paper, we investigate if individuals exhibit racial homophily when viewing visualizations, using mass shooting data in the United States as the example topic. We conducted a crowdsourced experiment (N=450) where each participant was shown a visualization displaying the counts of mass shooting victims, highlighting the counts for one of three racial groups (White, Black, or Hispanic). Participants were assigned to view visualizations highlighting their own race or a different race to assess the influence of racial concordance on changes in affect (emotion) and attitude towards gun control. While we did not find evidence of homophily, the results showed a significant negative shift in affect across all visualization conditions. Notably, political ideology significantly impacted changes in affect, with more liberal views correlating with a more negative affect change. Our findings underscore the complexity of reactions to mass shooting visualizations and suggest that future research should consider various methodological improvements to better assess homophily effects.