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He Votes or She Votes? Female and Male Discursive Strategies in Twitter Political Hashtags

机译:他投票还是她投票? Twitter政治标签中的男性和女性话语策略

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摘要

In this paper, we conduct a study about differences between female and male discursive strategies when posting in the microblogging service Twitter, with a particular focus on the hashtag designation process during political debate. The fact that men and women use language in distinct ways, reverberating practices linked to their expected roles in the social groups, is a linguistic phenomenon known to happen in several cultures and that can now be studied on the Web and on online social networks in a large scale enabled by computing power. Here, for instance, after analyzing tweets with political content posted during Brazilian presidential campaign,we found out that male Twitter users, when expressing their attitude toward a given candidate, are more prone to use imperative verbal forms in hashtags, while female users tend to employ declarative forms. This difference can be interpreted as a sign of distinct approaches in relation to other network members: for example, if political hashtags are seen as strategies of persuasion in Twitter, imperative tags could be understood as more overt ways of persuading and declarative tags as more indirect ones. Our findings help to understand human gendered behavior in social networks and contribute to research on the new fields of computer-enabled Internet linguistics and social computing, besides being useful for several computational tasks such as developing tag recommendation systems based on users' collective preferences and tailoring targeted advertising strategies, among others.
机译:在本文中,我们对在微博服务Twitter上发布时男女话语策略之间的差异进行了研究,特别关注政治辩论期间的主题标签指定过程。男女以不同的方式使用语言,回荡与他们在社会群体中预期角色相关的做法,这一事实是一种已知的语言现象,在几种文化中都会发生,现在可以在网络和在线社交网络中进行研究。强大的计算能力。例如,在这里,通过分析巴西总统竞选期间发布的带有政治内容的推文,我们发现男性Twitter用户在表达对特定候选人的态度时,更倾向于在命令标签中使用命令式口头形式,而女性用户则倾向于使用声明形式。可以将这种差异解释为与其他网络成员相关的独特方法的标志:例如,如果将政治主题标签视为Twitter中的说服策略,则命令性标签可以被理解为更公开的说服方式,而声明性标签则被视为更间接的方式。那些。我们的发现有助于理解社交网络中的性别行为,并有助于研究计算机支持的互联网语言学和社交计算的新领域,除了对一些计算任务(例如基于用户的集体偏好和开发标签推荐系统)有用有针对性的广告策略等。

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