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Sentiment analysis of the correlation between regular tweets and retweets

机译:常规推文与转发之间相关性的情感分析

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In this paper, we study the influence from the sentiment of regular tweets on retweeting. We propose a method to calculate the sentiment score for each tweet and each Twitter user. This method enables us to place the tweets and retweets into the same time period to explore the sentiment factor. We adopt the correlation coefficient between the sentiment scores of regular tweets and those of retweets to measure the influence. We categorize the Twitter users in three different ways to investigate three factors, which are the number of followers, betweenness centrality and the types of accounts. Community detection and machine learning are integrated into our approach. We find that the difference for correlation coefficients exists between different levels of the number of followers, and different types of users. Our method sheds a light on better predicting the dynamics of tweets diffusion by including the sentiment factor into the prediction model.
机译:在本文中,我们研究了常规推文情绪对转发的影响。我们提出一种方法来计算每个推文和每个Twitter用户的情感评分。这种方法使我们可以将推文和转推置于同一时间段,以探讨情感因素。我们采用常规推文和转发文集的情绪得分之间的相关系数来衡量影响。我们通过三种不同的方式对Twitter用户进行分类,以调查三个因素,即关注者数量,中间性和帐户类型。社区检测和机器学习已集成到我们的方法中。我们发现,相关系数的差异存在于不同级别的关注者数量和不同类型的用户之间。通过将情感因素纳入预测模型,我们的方法为更好地预测推文扩散动态提供了启示。

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