Burst Your Bubble! An Intelligent System for Improving Awareness of Diverse Social Opinions

Mingkun Gao, Hyo Jin Do, Wai-Tat Fu

Abstract: Social media users are overloaded with diverse opinions by people with opposing stances. Previous research shows that people often look for opinions that reinforce their pre-existing beliefs and stances, which may lead to social polarization. Traditional social media present opinions in a linear list format, which not only lacks structures for people to explore diverse viewpoints but also aggravates their selective exposure to agreeable opinions. To address this problem, we designed an intelligent system that improves awareness of diverse social opinions by providing visual hints and recommendations of opinions (e.g. news articles and comments) on different sides with different indicators. We evaluated our system with news articles about Obamacare repeal issue and their corresponding user comments from Facebook. Results demonstrate that our system could increase people»s awareness of their stances and opinion selection preferences, which mitigates selective exposure and thereby leads to a more balanced perception of social opinions.