Abstract
Nowadays, Twitter is one of the most used social networks with over 1.3 billion users. Twitter allows its users to write messages called tweets that now can contain up to 280 characters, having recently increased from 140 characters. Retweeting is Twitter’s key mechanism of information propagation. In this paper, we present a study on the importance of different text features in predicting the popularity of a tweet, e.g., number of retweets, as well as the importance of the user’s history of retweets. The resulting Retweet Predictive Model takes into account different types of tweets, e.g, tweets with hashtags and URLs, among the used popularity classes. Results show there is a strong relation between specific features, e.g, user’s popularity.
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Oliveira, N., Costa, J., Silva, C., Ribeiro, B. (2020). Retweet Predictive Model for Predicting the Popularity of Tweets. In: Madureira, A., Abraham, A., Gandhi, N., Silva, C., Antunes, M. (eds) Proceedings of the Tenth International Conference on Soft Computing and Pattern Recognition (SoCPaR 2018). SoCPaR 2018. Advances in Intelligent Systems and Computing, vol 942. Springer, Cham. https://doi.org/10.1007/978-3-030-17065-3_19
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DOI: https://doi.org/10.1007/978-3-030-17065-3_19
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