Sentiment analysis of the correlation between regular tweets and retweets - Chen, Jundong; Li, He; Wu, Zeju; Hossain, Md Shafaeat (Institute of Electrical and Electronics Engineers Inc., 2017)
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. © 2017 IEEE.
Keywords: Artificial intelligence; Betweenness centrality; Community detection; Correlation coefficient; Data mining; Learning systems; Prediction model; Sentiment analysis; Sentiment scores; Social networking (online); Time-periods; Twitter classification; dept.csc; machine learning; sentiment analysis; social network