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SoCS: Assessing Information Credibility Without Authoritative Sources

SoCS: Assessing Information Credibility Without Authoritative Sources
SoCS:在没有权威来源的情况下评估信息可信度
批准号:
0968489
负责人:
Qiaozhu Mei
金额:
$75.0万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2010
资助国家:
美国
项目状态:
已结题
起止时间:
2010-07-01 至 2015-06-30

项目摘要

项目成果

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中文摘要
翻译
谣言、诽谤和阴谋论现在可以通过电子邮件、博客和其他社交媒体迅速传播。此类信息的接收者不得质疑其有效性。此外,即使经过仔细的调查和思考,也不是每个人都同意特定主张的有效性。该项目将开发工具,帮助人们对可信度进行个人评估。我们的目标是尽量减少“社会不可信性”的数量,而不是依赖特定的来源作为地面事实的权威仲裁者。也就是说,该工具将识别“类似”人(经过仔细考虑,过去有人倾向于同意的人)不相信的断言,或者来自某人倾向于不同意的来源。将开发一个在线媒体的文本挖掘系统,以提取有争议的断言和用户对这些断言所表达的信念。关于常见断言的信念的比较,以及信念的撤回或更新,将作为个性化声誉度量的一部分进行跟踪。这项工作是第一次尝试正式解决基于文本挖掘和社会计算系统的信息可信度自动评估。这些技术将为信息检索和信誉网络中许多具有挑战性的研究问题提供解决方案。这些技术广泛适用于关注内容的可信度和来源的声誉的其他领域,以帮助广泛的信息消费者。 原型工具将在高中免费发布和展示,从而围绕公众感兴趣的主题建立对信仰多样性的认识。
英文摘要
Rumors, smears, and conspiracy theories can now spread quickly through email, blogs, and other social media. Recipients of such messages may not question their validity. Moreover, even upon careful investigation and reflection, not everyone will agree about the validity of particular claims. This project will develop tools that help people make personal assessments of credibility. Rather than relying on particular sources as authoritative arbiters of ground truth, the goal is to minimize the amount of "social implausibility." That is, the tool will identify assertions that are disbelieved by "similar" people (those who, after careful consideration, someone tended to agree with in the past) or come from sources that someone has tended to disagree with. A text mining system for online media will be developed to extract controversial assertions and the beliefs expressed by users about those assertions. Comparisons of beliefs about common assertions, and retractions or updates to beliefs, will be tracked as part of personalized reputation measures.This work is the first attempt to formally address the automatic assessment of information credibility based on text mining and social computational systems. The techniques will provide the solution to many challenging research problems in information retrieval and reputation networks. The techniques are broadly applicable to other domains where the credibility of content and reputation of sources is a concern, to help a broad class of information consumers. Prototype tools will be released freely and demonstrated in high schools, thereby building awareness of the diversity of beliefs around topics of public interest.
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