Abstract
An efficient tweet dissemination predictor for retweets and replies is central both to a better understanding of influentials (people and messages), as well as of how social media revenue models can be better monetized. Traditionally research concentrated on retweets popularity and information cascades while neglecting the importance of features richness and classification. We propose a novel approach that introduces feature planes for better prediction of single step tweet dissemination. We show that our model can achieve a quasi-perfect prediction. This promises to be a seminal step towards a better understanding of data dissemination in social networks.
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References
Arnaboldi, V., Conti, M., Passarella, A., Pezzoni, F.: Ego networks in twitter: an experimental analysis. In: Proceedings of IEEE INFOCOM, pp. 3459–3464 (2013)
Boyd, D., Golder, S., Lotan, G.: Tweet, tweet, retweet: Conversational aspects of retweeting on twitter. In: System Sciences (HICSS), 2010 43rd Hawaii International Conference on, pp. 1–10. IEEE (2010)
Chen, K., Chen, T., Zheng, G., Jin Ou and Yao, E., Yu, Y.: Collaborative personalized tweet recommendation. In: Proceedings of the 35th international ACM SIGIR conference on Research and development in information retrieval, pp. 661–670 (2012)
Cheng, J.C., Adamic, L., Dow, A.P., Kleinberg, H.M., Leskovec, J.: Can cascades be predicted? In: Proceedings of the 23rd international conference on World wide web, pp. 925–936 (2014)
Ferrara, E., Yang, Z.: Quantifying the effect of sentiment on information diffusion in social media. In: ArXiv preprints (2015)
Galuba, W., Aberer, K., Chakraborty, D., Despotovic, Z., Kellerer, W.: Outtweeting the twitterers - predicting information cascades in microblogs. In: Proceedings of the 3rd Wonference on Online social networks, pp. 3–3 (2010)
Gan, D., Jenkins, L.R.: Social networking privacywhos stalking you? Future Internet 7(1), 67–93 (2015)
Hoang, T.A., Lim, E.P.: Virality and susceptibility in information diffusions. In: Sixth International AAAI Conference on Weblogs and Social Media (2012)
Hong, L., Doumith, A., Davison, B.D.: Personalized retweet prediction in twitter. In: 4th Workshop on Information in Networks (2012)
Kelley, P.G., Cranshaw, J.: Conducting research on twitter: A call for guidelines and metrics (2013)
Martin, T., Hofman, J.M., Sharma, A., Anderson, A.,Watts, D.J.: Exploring limits to prediction in complex social systems. In: Proceedings of the 25th International Conference on World Wide Web, pp. 683–694 (2016)
Myers, S.A., Zhu, C., Leskovec, J.: Information diffusion and external influence in networks. In: Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining, pp. 33–41 (2012)
Petrovic, S., Osborne, M., Lavrenko, V.: Rt to win! predicting message propagation in twitter. In: ICWSM (2011)
Pezzoni, F., An, J., Passarella, A., Crowcroft, J., Conti, M.: Why do i retweet it? an information propagation model for microblogs. In: Proceedings of the 5th International Conference on Social Informatics, pp. 360–369 (2013)
Salganik, M.J., Dodds, P.S., Watts, D.J.: Experimental study of inequality and unpredictability in an artificial cultural market. Science 311(5762), 854–856 (2006)
Yang, J., Counts, S.: Predicting the speed, scale, and range of information diffusion in twitter. In: In 4th International AAAI Conference on Weblogs and Social Media (2010)
Yuan, N.J., Zhong, Y., Zhang, F., Xie, X., Lin, C.Y., Rui, Y.: Who will reply to/retweet this tweet?: The dynamics of intimacy from online social interactions. In: Proceedings of the Ninth ACM International Conference on Web Search and Data Mining, pp. 3–12 (2016)
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Garg, K., Arnaboldi, V., Giordano, S. (2017). A Novel Approach to Predict Retweets and Replies Based on Privacy and Complexity-Aware Feature Planes. In: Cherifi, H., Gaito, S., Quattrociocchi, W., Sala, A. (eds) Complex Networks & Their Applications V. COMPLEX NETWORKS 2016 2016. Studies in Computational Intelligence, vol 693. Springer, Cham. https://doi.org/10.1007/978-3-319-50901-3_37
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DOI: https://doi.org/10.1007/978-3-319-50901-3_37
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