SeCredISData 2018:社交数据中信息的情感、情感和可信度专题会议

F. Benamara, C. Bosco, E. Fersini, G. Pasi, V. Patti, Marco Viviani
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引用次数: 0

摘要

如今,社交网络代表了通过Web 2.0技术支持和促进人们之间的社交互动的主要手段。个人通过交换多种内容(即文字、声音、视觉),在虚拟社区中进行互动,以追求共同的兴趣或目标,即所谓的用户生成内容(UGC)。在此背景下,SeCredISData特别会议特别致力于讨论大社会数据分析对从不同角度解决与社会有关的公开问题的影响。一方面,有必要推进情感和情感的研究,探索情感认知模型及其与智能系统集成的可能性。另一方面,在一个可信中介已经消失,人们只能依靠自己的认知能力来判断信息的时代,迫切需要解决在线信息可信度评估问题。因此,特别会议的目的是促进能够解决这些问题的模式和应用的发展。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
SeCredISData 2018: Special Session on Sentiment, Emotion, and Credibility of Information in Social Data
The Social Web represents nowadays the principal means to support and foster social interactions among people through Web 2.0 technologies. Individuals interact in virtual communities to pursue mutual interests or goals, by exchanging multiple kinds of contents (i.e., textual, acoustic, visual), the so-called User-Generated Content (UGC). In this context, the SeCredISData Special Session is especially devoted at discussing the implications that the analysis of big social data has in tackling open issues related to society from different perspectives. On one side, there is the need to push forward the research on emotion and sentiment, and the investigation of affective cognitive models and their possible integration into intelligent systems. On the other side, it is urgent to address the issue of on-line information credibility assessment, in an era where trusted intermediaries have disappeared and people must rely only on their cognitive capacities to judge information. The Special Session is therefore aimed at promoting the development of models and applications able to tackle these issues.
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