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| Content Provider | ACM Digital Library |
|---|---|
| Author | Do, Hyo Jin |
| Abstract | Despite the explosive growth of online social media where people can easily share their thoughts, our current society is more divided than before, gridlocked over society, culture, race, and gender issues. Selective exposure, a confirmatory bias of individuals that favors preexisting opinions while avoiding attitude-inconsistent views, impedes the balanced insight of a controversial issue, which thereby would account for the societal division. In this research proposal, we introduce an intelligent interface that automatically clusters and visualizes diverse opinions about a controversial topic. First, we collect controversial posts from Facebook and its comments. Then, the comments are automatically clustered using a machine-learning algorithm based on features that reflect its contents and the writer's stance. Lastly, we propose an intelligent user interface with controversial posts and opinion clusters where users would be motivated to hunt for opinion groups that are different from their own perspective. |
| Starting Page | 217 |
| Ending Page | 220 |
| Page Count | 4 |
| File Format | |
| ISBN | 9781450348935 |
| DOI | 10.1145/3030024.3040991 |
| Language | English |
| Publisher | Association for Computing Machinery (ACM) |
| Publisher Date | 2017-03-07 |
| Publisher Place | New York |
| Access Restriction | Subscribed |
| Subject Keyword | Intelligent user interface Social opinion Machine-learning |
| Content Type | Text |
| Resource Type | Article |
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