Journal of Guangxi Normal University(Natural Science Edition) ›› 2026, Vol. 44 ›› Issue (1): 80-90.doi: 10.16088/j.issn.1001-6600.2024122103

• Intelligence Information Processing • Previous Articles     Next Articles

Fake News Detection with Integrated Emotional Knowledge

HUANG Qi, LI Bixin, WANG Mingwen*, XIAO Cong, LIU Jing, LOU Wenbing   

  1. School of Computer and Information Engineering, Jiangxi Normal University, Nanchang Jiangxi 330022, China
  • Received:2024-12-21 Revised:2025-03-26 Online:2026-01-05 Published:2026-01-26

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Abstract: Emotion plays a significant role in fake news detection. Existing research mainly focuses on extracting emotional features from a linguistic perspective, which fails to explore the relationships between emotions from a psychological perspective.In addition, the connection between sentiment features and text features is ignored by existing work, and the potential semantic information of news can not be explored fully. To address the above issues, a fake news detection mode(FNEK) is proposed by this paper, which integrates psychological and emotional knowledge. The Plutchik’s wheel of emotions theory from psychology is incorporated by the model to extract emotional features, and the emotional features are combined with textual features from local and global perspectives, which enhances the accuracy and reliability of fake news detection.Experimental results on publicly available Politifact, Weibo16, and Weibo20 datasets show that the proposed model improves accuracy by 2.1, 0.7 and 2.5 percentage points, respectively, compared with state-of-the-art baseline models.

Key words: fake news detection, linguistic perspective, psychological perspective, emotional knowledge, Plutchik’s wheel of emotions

CLC Number:  TP391.1
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