Data Portraits: Connecting People of Opposing Views

TL;DR

This paper proposes a visualization-based approach to connect users of opposing views on social networks by suggesting relevant content from dissimilar users, aiming to reduce polarization and negative emotional reactions.

Contribution

It introduces a novel organic visualization paradigm for data portraits that effectively presents opposing views and mitigates negative emotional effects of content recommendations.

Findings

Organic visualization reduces negative emotional reactions to opposing content.

Recommending relevant content from dissimilar users can foster connections.

Significant individual differences affect how users perceive recommendations.

Abstract

Social networks allow people to connect with each other and have conversations on a wide variety of topics. However, users tend to connect with like-minded people and read agreeable information, a behavior that leads to group polarization. Motivated by this scenario, we study how to take advantage of partial homophily to suggest agreeable content to users authored by people with opposite views on sensitive issues. We introduce a paradigm to present a data portrait of users, in which their characterizing topics are visualized and their corresponding tweets are displayed using an organic design. Among their tweets we inject recommended tweets from other people considering their views on sensitive issues in addition to topical relevance, indirectly motivating connections between dissimilar people. To evaluate our approach, we present a case study on Twitter about a sensitive topic in Chile, where we estimate user stances for regular people and find intermediary topics. We then evaluated our design in a user study. We found that recommending topically relevant content from authors with opposite views in a baseline interface had a negative emotional effect. We saw that our organic visualization design reverts that effect. We also observed significant individual differences linked to evaluation of recommendations. Our results suggest that organic visualization may revert the negative effects of providing potentially sensitive content.