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Sentiment leaning of influential communities in social networks

机译:社交网络中有影响力社区的情感倾向

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Abstract Social media and social networks contribute to shape the debate on societal and policy issues, but the dynamics of this process is not well understood. As a case study, we monitor Twitter activity on a wide range of environmental issues. First, we identify influential users and communities by means of a network analysis of the retweets. Second, we carry out a content-based classification of the communities according to the main interests and profile of their most influential users. Third, we perform sentiment analysis of the tweets to identify the leaning of each community towards a set of common topics, including some controversial issues. This novel combination of network, content-based, and sentiment analysis allows for a better characterization of groups and their leanings in complex social networks.
机译:摘要社交媒体和社交网络有助于形成有关社会和政策问题的辩论,但是这一过程的动态性尚不为人所知。作为案例研究,我们监视Twitter在广泛的环境问题上的活动。首先,我们通过对转发进行网络分析来确定有影响力的用户和社区。第二,我们根据社区的主要兴趣和影响力最大的用户的个人资料对社区进行基于内容的分类。第三,我们对推文进行情感分析,以确定每个社区对一系列常见主题(包括一些有争议的问题)的倾向。网络,基于内容的分析和情感分析的这种新颖组合可以更好地表征群体及其在复杂的社交网络中的倾向。

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