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: $ 75万
• 依托单位: Regents of the University of Michigan - Ann Arbor
• 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
• 起止时间: 2010-07-01 至 2015-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0968489&HistoricalAwards=false
• 关键词: SoCS; Assessing; Information; Credibility; Without

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.

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。接收此类信息的人不得质疑其有效性。此外，即使经过仔细的调查和反思，也不是每个人都会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。与其依赖特定的消息来源作为事实的权威仲裁者，其目标是尽量减少“社会不可信”的数量。也就是说，该工具将识别“相似”的人（经过仔细考虑，某人过去倾向于同意的人）不相信的断言，或者来自于某人倾向于不同意的来源。本文将开发一个用于网络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表达的信念。对常见断言的信念比较，以及信念的撤回或更新，将作为个性化声誉测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其他领域，其中内容的可信度和来源的声誉是一个问题，以帮助广大类别的信息消费者。原型工具将免费发布，并在高中展示，从而建立围绕公共利益主题的信仰多样性意识。