【24h】

Detecting Rumor and Disinformation by Web Mining

机译:通过网挖掘检测谣言和虚假信息

获取原文

摘要

A method to detect if a given text is a rumor or disinformation is proposed, based on web mining and linguistic technology comparing two paragraphs of text. We hypothesize about a family of content generation algorithms which are capable of producing disinformation from a portion of genuine text. We then propose a disinformation detection algorithm which finds a candidate source of text on the web and compares it with the given text, applying parse thicket technology. Parse thicket is graph combined from a sequence of parse trees augmented with inter-sentence relations for anaphora and rhetoric structures. We evaluate our algorithm in the domain of customer reviews, considering a product review as an instance of possible disinformation. It is confirmed as a plausible way to detect rumor and disinformation in a web document.
机译:基于网络挖掘和语言技术,提出了一种检测给定文本是否是谣言或虚假信息的方法,比较两段文本。我们假设一系列内容生成算法,其能够从正版文本的一部分产生欺骗。然后,我们提出了一种虚拟的检测算法,该算法在网上找到候选文本的候选源,并将其与给定文本进行比较,应用解析丛林技术。解析丛林是曲线图,从一系列解析树中加强了句子和修辞结构的句子关系。我们在客户评论领域中评估我们的算法,考虑产品审查作为可能的禁令的一个实例。它被确认为在Web文档中检测谣言和虚假信息的合理方式。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号