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Content Feature Enrichment for Analyzing Trust Relationships in Web Forums

机译:内容功能丰富,用于分析网络论坛中的信任关系

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As criminals and terrorist employ social media platforms for planning and executing nefarious activities, understanding the degree of trustworthiness in interactions among actors becomes crucial for detecting their activities. Measuring trust in these environments can benefit analysts who are monitoring web forums to detect criminal or terrorist activities. Previous research proposed a trust model that could enable automatic trust discovery using speech act theory. This paper introduces a new classification method that enriches traditional techniques with contextual information. We conducted experiments to compare the proposed method with traditional approaches. The results show that the proposed method outperforms other alternative methods.
机译:作为犯罪分子和恐怖分子雇用社交媒体平台进行规划和执行邪恶的活动,了解参与者之间的相互关系的责任程度对检测他们的活动至关重要。在这些环境中衡量信任可以利用正在监控网络论坛以检测刑事或恐怖活动的分析师。以前的研究提出了一种信任模型,可以使用语音法理论实现自动信任发现。本文介绍了一种新的分类方法,可以丰富具有语境信息的传统技术。我们进行了实验,比较了具有传统方法的提出的方法。结果表明,所提出的方法优于其他替代方法。

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