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Fusing Multi-Features for Rumor tweets detection in Wechat

机译:在微信中融合谣言推文检测的多个功能

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Recently, rumor detection has attracted lots of research interest because of the quick development of social networks and the widely spread of rumor. The exiting studies is mainly about the open social network such as Weibo and Facebook. However, there is little research about closed social networks, especially Wechat. As a famous app with more than one billion daily active user, the tweets in Wechat can attract lots of attention, which gives the spread of rumor tweets more chance. In this paper, we empirically study the tweets spread in Wechat. We first analyze the text information and users’ behavior of Wechat tweets, then we come up with several important features needed for rumor detection. Furthermore, we propose a new model which can capture the impact of both users’ behavior and text information. We conduct experiments using a large tweets dataset collected in Wechat, the result shows that our proposed method can effectively detect the rumor tweets.
机译:最近,谣言检测吸引了许多研究兴趣,因为社交网络的快速发展和谣言广泛传播。 退出的研究主要是关于Weibo和Facebook等开放的社交网络。 然而,关于封闭的社交网络,特别是微信的几乎没有研究。 作为一个有超过10亿日常活跃用户的着名应用程序,微信中的推文可以吸引很多关注,这使得谣言推文的传播更多的机会。 在本文中,我们凭经验研究了微信蔓延的推文。 我们首先分析微信推文的文本信息和用户行为,然后我们提出了谣言检测所需的几个重要功能。 此外,我们提出了一种新模型,可以捕获用户行为和文本信息的影响。 我们使用在微信中收集的大鸣叫数据集进行实验,结果表明我们所提出的方法可以有效地检测谣言推文。

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