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Debate on Political Reforms in Twitter: A Hashtag-driven Analysis of Political Polarization

机译:关于Twitter中的政治改革的辩论:政治极化的哈希特驱动分析

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Political debates about a reform may sparkle national controversies, by leading members of the community to polarize their opinions and sentiment about the topic addressed. With the rise of social media like Twitter users are encouraged to voice and share their strong and polarized views and in general people are exposed to broader viewpoints than they were before. The large amount of user-generated social data available is a great opportunity to investigate the communicative behaviors emerging in the context of such political debates and to shed some light on the way communities of users with different roles in the society and different political sentiment interact. In this paper we focussed on communications in Twitter around the reform of marriage in France in 2012 and 2013 - "Le Mariage Pour Tous" - which had been the subject of debate and controversy. We collected a corpus of tweets tagged by the hashtag #mariagepourtous, created to mark the messages about the reform. We applied different kinds of analysis on our dataset based on linguistic and non linguistic features of the observed data in order to investigate the communicative behavior in using subjective and evaluative language on a political topic. The analysis leaded also to reflect on the impact of different typologies of users involved in the virtual debate which included both political messages created by media organizations and by other individual users, from ordinary citizens to politicians or celebrities.
机译:关于改革的政治辩论可能会闪耀国家争议,通过社会领导成员,使他们的意见和情绪偏离有关讨论的主题。随着社交媒体的兴起,如推特用户被鼓励声音和分享他们的强大和偏振的观点,并且一般人们接触到更广泛的观点来看。可用的大量用户生成的社会数据是调查在这些政治辩论的背景下出现的交际行为的绝佳机会,并在社会中不同角色的社区和不同的政治情感界面阐明了一些光线。在本文中,我们在2012年和2013年在法国的婚姻改革周围介绍了Twitter的通信 - “Le Mariage倾倒” - 这是辩论和争议的主题。我们收集了由HashTag标记的推文的语料库#maragepourtous,创建以标记有关改革的消息。基于观察到的数据的语言和非语言特征,我们在我们的数据集上应用了不同类型的分析,以调查在政治主题上使用主观和评估语言的交际行为。该分析还涉及反映了涉及虚拟辩论的不同类型的影响,这些内容包括媒体组织和其他个人用户从普通公民到政治家或名人创造的政治信息。

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