Social Information Retrieval

社会信息检索

• 批准号: 1000233085-2019
• 负责人: Bagheri, Ebrahim
• 金额: $ 1.82万
• 依托单位: Ryerson University
• 依托单位国家: 加拿大
• 项目类别: Canada Research Chairs
• 财政年份: 2020
• 资助国家: 加拿大
• 起止时间: 2020-01-01 至 2021-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=695629
• 关键词: Social; Information; Retrieval

This proposed program will strategically address the increasing challenge of misinformation while providing foundational contributions in social information retrieval. From a practical perspective, it endeavors to (1) semantically model misinformation and identify causal relations between real-world events and misinformation in online platforms, and (2) effectively retrieve factual information counter to misinformation and selectively present it to optimize uptake. From a theoretical view, it will develop techniques to (1) model topically-focused temporal textual corpora in the context of knowledge graphs for measuring semantic association and causal relations, and (2) effectively retrieve content by considering aspects of coverage, trust, persuasion, and discord.

该计划将从战略上解决日益增长的错误信息挑战，同时为社会信息检索提供基础性贡献。从实践的角度来看，它致力于（1）语义建模错误信息，并识别真实世界事件与在线平台错误信息之间的因果关系，（2）有效地检索与错误信息相反的事实信息，并有选择地呈现它以优化吸收。从理论角度来看，它将开发技术来（1）在知识图的背景下对以主题为中心的时间文本语料库进行建模，以测量语义关联和因果关系，以及（2）通过考虑覆盖率，信任，说服力和不和谐等方面来有效地检索内容。