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Using Sentiment Induction to Understand Variation in Gendered Online Communities

机器翻译利用情感归纳理解性别在线社区的变异

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3.3 【6hr】

【摘要】We analyze gendered communities defined in three different ways: text, users, and sentiment. Differences across these representations reveal facets of communities' distinctive identities, such as social group, topic, and attitudes. Two communities may have high text similarity but not user similarity or vice versa, and word usage also does not vary according to a clearcut, binary perspective of gender. Community-specific sentiment lexicons demonstrate that sentiment can be a useful indicator of words' social meaning and community values, especially in the context of discussion content and user demographics. Our results show that social platforms such as Reddit are active settings for different constructions of gender.

【作者】Li Lucy; Julia Mendelsohn;

【作者单位】Symbolic Systems Program Department of Computer Science Stanford University; Department of Linguistics Department of Computer Science Stanford University;

【年(卷),期】2019,,

【页码】156-166

【总页数】11

【正文语种】eng

【中图分类】;

【关键词】;