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Emotional polarity about users of social networking systems

机译:关于社交网络系统用户的情感极性

摘要

A social networking system infers a sentiment polarity of a user toward content of a page. The sentiment polarity of the user is inferred based on received information about an interaction between the user and the page (e.g., like, report, etc.), and may be based on analysis of a topic extracted from text on the page. The system infers a positive or negative sentiment polarity of the user toward the content of the page, and that sentiment polarity then may be associated with any second or subsequent interaction from the user related to the page content. The system may identify a set of trusted users with strong sentiment polarities toward the content of a page or topic, and may use the trusted user data as training data for a machine learning model, which can be used to more accurately infer sentiment polarity of users as new data is received.
机译:社交网络系统推断用户对页面内容的情感极性。基于接收到的关于用户与页面之间的交互的信息(例如,诸如报告等)来推断用户的情感极性,并且可以基于对从页面上的文本中提取的主题的分析。系统向页面内容推断用户的正面或负面情绪极性,然后该情绪极性可以与用户与页面内容有关的任何第二或后续交互关联。该系统可以识别对页面或主题的内容具有强烈的情感极性的一组可信用户,并且可以将可信的用户数据用作机器学习模型的训练数据,该机器学习模型可以用来更准确地推断用户的情感极性。当收到新数据时。

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