Unsupervised rumor detection based on users’ behaviors using neural networks
Online social networks have become the hotbeds of many rumors as information can propagate much faster than ever. In order to detect the few but potentially harmful rumors to prevent the public issues they may cause, we propose an unsupervised learning model combining Recurrent Neural Networks and A...
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| Main Authors: | , , , , |
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| Other Authors: | |
| Format: | Article |
| Language: | English |
| Published: |
2020
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| Subjects: | |
| Online Access: | https://hdl.handle.net/10356/138244 |
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| Institution: | Nanyang Technological University |
| Language: | English |