Data Portraits: Connecting People of Opposing Views
ABSTRACT Social networks allow people to connect with each otherand have conversations on a wide variety of topics. How-ever, users tend to connect with like-minded people and readagreeable information, a behavior that leads to group polar-ization. Motivated by this scenario, we study how to takeadvantage of partial homophily to suggest agreeable contentto users authored by people with opposite views on sensitiveissues. We introduce a paradigm to present a data portraitof users, in which their characterizing topics are visualizedand their corresponding tweets are displayed using an or-ganic design. Among their tweets we inject recommendedtweets from other people considering their views on sensitiveissues in addition to topical relevance, indirectly motivatingconnections between dissimilar people. To evaluate our ap-proach, we present a case study on Twitter about a sensitivetopic in Chile, where we estimate user stances for regularpeople and nd intermediary topics. We then evaluated ourdesign in a user study. We found that recommending topi-cally relevant content from authors with opposite views in abaseline interface had a negative emotional e ect. We sawthat our organic visualization design reverts that e ect. Wealso observed signi cant individual di erences linked to eval-uation of recommendations. Our results suggest that organicvisualization may revert the negative e ects of providingpotentially sensitive content.