Enhancing rumour classification with target-based dual emotion using LLM
Emotion plays a significant role in detecting online rumours. While existing methods focus on publisher emotion, the emotions of readers (i.e., reader emo tion) are often overlooked. Moreover, the relationship between publisher emotion and reader emotion (i.e., dual emotion) and its manifestation i...
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| Format: | Thesis-Master by Coursework |
| Language: | English |
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Nanyang Technological University
2024
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| Online Access: | https://hdl.handle.net/10356/181072 |
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| Institution: | Nanyang Technological University |
| Language: | English |