Value-Based Retweet Prediction on Twitter

Surbhi Kakar, Deepali Dhaka, Monica Mehrotra


Retweeting is an online activity done on the twitter social network. This activity leads to sharing of opinions and ideas from one person to another. Predicting retweet decision has been an interesting and challenging task since the past decade. Past studies have shown that emotions, sentiments and topic specific emotions can influence the retweet decision of the user. However, value systems of an individual can also be an important and crucial aspect in predicting the decision of user. Hence, through our work, we propose to study retweet prediction as a function of value systems. Our work also presents an experimental comparative study with the features used in previous studies. The experimental results using the different machine learning algorithms shows that value-systems have a higher performance in predicting retweet decision of the user as compared to emotions, sentiments and topic-specific emotions.

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