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Content feature enrichment for analyzing trust relationships in web forums

机译:内容功能丰富,可用于分析Web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:随着犯罪分子和恐怖分子使用社交媒体平台来计划和执行邪恶活动,了解参与者之间互动中的可信度对于检测他们的行为至关重要。在这些环境中衡量信任度可以使监视网络论坛以检测犯罪或恐怖活动的分析师受益。先前的研究提出了一种信任模型,该模型可以使用语音行为理论实现自动信任发现。本文介绍了一种新的分类方法,该方法通过上下文信息丰富了传统技术。我们进行了实验,以将所提出的方法与传统方法进行比较。结果表明,该方法优于其他方法。

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