Name
Title | ||
|---|---|---|
Rumor Detection on Social Media Using Temporal Dynamic Structure and Emotional Information |
Abstract | ||
|---|---|---|
Social Media has become main platform for the public to obtain information in recent years. Meanwhile, growing rumors are also generated and wildly spread, which may cause critical damage on individuals and the society. Existing methods of rumor detection have concentrated on extracting features only from text content, user profiles, temporal information, and structural information. However, few related methods have focused on the variation of propagation structure over time. Moreover, rumor detection is also bound up with sentiment analysis. Yet, to the best of our knowledge, exploiting emotional information is little investigated. To alleviate these issues, we propose a novel model for effectively detecting rumor, by utilizing two characteristics: temporal dynamic structure and emotional information. The model incorporates the emotional features into temporal dynamic features to train a reliable fused classifier. We have conducted extensive experiments on a real-world dataset and the results show that our model achieves a better performance than several state-of-the-art methods. |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1109/DSC53577.2021.00010 | 2021 IEEE Sixth International Conference on Data Science in Cyberspace (DSC) |
Keywords | DocType | ISBN |
Rumor Detection,Temporal Dynamic Structure,Emotional Information,Social Network | Conference | 978-1-6654-1816-4 |
Citations | PageRank | References |
0 | 0.34 | 12 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Chenming Wang | 1 | 0 | 0.34 |
| Bin Zhou | 2 | 341 | 30.99 |
| Hongkui Tu | 3 | 0 | 1.01 |
| Yujia Liu | 4 | 0 | 0.34 |