Integrating Semantic and Structural Information with Graph Convolutional Network for Controversy Detection (2020.acl-main)
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| Challenge: | Existing methods for identifying controversial posts on social media are limited . existing methods fail to incorporate semantic information from content-related posts . |
| Approach: | They propose a method to integrate the information from topics, posts, and comments . they extend their model to Disentangled TPC-GCN to disentangle topic-related features . |
| Outcome: | The proposed method outperforms existing methods on two real-world datasets. |
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