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.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Park, H., Kwak, H., Lee, C., Moon, S.: What is Twitter, a social network or a news media? In: 19th International World Wide Web Conference (WWW 2010) (2010)
Petrovic, S., Osborne, M., Lavrenko, V.: Rt to win! Predicting message propagation in Twitter. In: Proceedings of the Fifth International Conference on Weblogs and Social Media, Catalonia, Spain, Barcelona (2011)
Kasneci, G., Jenders, M., Naumann, F.: Analyzing and predicting viral tweets. In: Association for Computing Machinery, pp. 657–664 (2013)
Xu, Z., Zhang, Y., Yang, Q.: Predicting popularity of messages in Twitter using a feature-weighted model. Int. J. Adv. Intell. (2012)
He, H.Y., Rajaraman, A., Zhao, Q., Erdogdu,. M.A., Leskovec, J.: A self-exciting point process model for predicting tweet popularity. In: Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD 2015, pp. 1513–1522 (2015)
Wu, B., Shen, H.: Analyzing and predicting news popularity on Twitter. Int. J. Inf. Manag. 35, 702–711 (2015)
Nitins, T., Burgess, J.: Twitter, brands, and user engagement. Twitter Soc. 89, 293–304 (2014)
Pirolli, P., Suh, B., Hong, L., Chi, E.H.: Want to be retweeted? Large scale analytics on factors impacting retweet in twitter network. In: Proceedings of the 2nd IEEE International Conference on Social Computing, SOCIALCOM, pp. 177–184 (2010)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2020 Springer Nature Switzerland AG
About this paper
Cite this paper
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
Download citation
DOI: https://doi.org/10.1007/978-3-030-17065-3_19
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-17064-6
Online ISBN: 978-3-030-17065-3
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)