摘要
Rumors in social media represent a severe problem prevailing in today's society. Previous studies on automated rumor detection have shown that the topological information specific to social media is a vital clue for debunking rumors. However, existing automatic rumor detection approaches either oversimplify the graph structure or ignore this crucial clue. To address this issue, we propose a model that explores homogeneity and conversation structure to identify rumors. Our model learns more comprehensive and precise representations by modeling follower-following relationships of users, simulating the propagation layout of tweets, and connecting responders' behavior. The experimental results on two public Twitter datasets show that our model's performance outperforms other state-of-the-art baseline models. Furthermore, the experimental results prove our hypothesis that birds of a feather rumor together. The results demonstrate that both the conversation structure and the friend network's homogeneity are significant for checking the veracity of a suspicious tweet.
原文 | English |
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文章編號 | 9268937 |
頁(從 - 到) | 212865-212875 |
頁數 | 11 |
期刊 | IEEE Access |
卷 | 8 |
DOIs | |
出版狀態 | Published - 2020 |
All Science Journal Classification (ASJC) codes
- 一般電腦科學
- 一般材料科學
- 一般工程