社会网络信息的可信度问题近年来受到了相当大的关注。谣言的散播可能造成社会恐慌,引发信任危机。在国内,新浪微博用户量的快速增长,使其成为了谣言传播的温床。及时清理在新浪微博中传播的谣言,对于社会的和谐发展有着现实的意义。该文以新浪微博为背景,将谣言检测任务作为分类问题,首次提出将微博评论的情感倾向作为谣言检测分类器的一项特征。实验结果表明,引入评论的评论情感倾向特征后,使得谣言检测的分类结果得到了可观的提升。
Abstract
The problem of reliability of social network information has received considerable attention in recent years. Malicious rumors may cause social panic, even triggering a crisis of confidence. In China, the rapid growth of Sina Weibo user quantity paves the way for the spread of rumors. It has significant practical meaning for the harmonious society to clean up rumors in Sina Weibo in time. Here we consider the rumor detection task as a classification problem and propose a method by using the emotional tendencies of micro-blog comments as a feature. The experimental results show that the comments emotion brings a considerable improvement.
关键词
新浪微博 /
谣言检测 /
SVM /
情感计算
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Key words
Sina Weibo /
rumor detection /
SVM /
affective computing
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参考文献
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脚注
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基金
国家自然科学基金(61632011,61572102,61562080)
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