融合情感知识的虚假新闻检测

doi:10.16088/j.issn.1001-6600.2024122103

摘要/Abstract

摘要： 情感在虚假新闻检测中起着重要作用。现有工作侧重于从语言学角度挖掘情感特征,忽视了从心理学角度挖掘情感特征,导致不能挖掘情感之间的关联信息;此外,现有工作忽略了情感特征与文本特征之间的联系,导致不能充分挖掘新闻潜在语义关系。为解决上述问题,本文提出一种融合心理学情感知识的虚假新闻检测模型(FNEK),旨在将Plutchik情感轮心理学模型引入虚假新闻检测领域,利用其提取情感特征,同时通过局部和全局视角提取文本特征,并与情感特征融合进行虚假新闻检测,以提高虚假新闻检测模型的准确性和可靠性。在公开的 Politifact、Weibo16和Weibo20数据集上的实验结果表明,本文模型与当前先进模型相比,在准确率上分别提高2.1、0.7和2.5个百分点。

关键词: 虚假新闻检测, 语言学, 心理学, 情感知识, Plutchik情感轮

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

中图分类号: TP391.1

黄琪, 李必镡, 王明文, 肖聪, 刘璟, 罗文兵. 融合情感知识的虚假新闻检测[J]. 广西师范大学学报（自然科学版）, 2026, 44(1): 80-90.

HUANG Qi, LI Bixin, WANG Mingwen, XIAO Cong, LIU Jing, LOU Wenbing. Fake News Detection with Integrated Emotional Knowledge[J]. Journal of Guangxi Normal University(Natural Science Edition), 2026, 44(1): 80-90.

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