Prediction of retweet cascade size over time.

Kupavskii A.; Ostroumova L.; A. Umnov; Usachev S.; Serdyukov P.; Gusev G.; Kustarev A.

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Prediction of retweet cascade size over time.

P. 2335–2338.

Kupavskii A., Ostroumova L., Umnov A., Usachev S., Serdyukov P., Gusev G., Kustarev A.

Retweet cascades play an essential role in information diffusion in Twitter. Popular tweets reflect the current trends in Twitter, while Twitter itself is one of the most important online media. Thus, understanding the reasons why a tweet becomes popular is of great interest for sociologists, marketers and social media researches. What is even more important is the possibility to make a prognosis of a tweet's future popularity. Besides the scientific significance of such possibility, this sort of prediction has lots of practical applications such as breaking news detection, viral marketing etc. In this paper we try to forecast how many retweets a given tweet will gain during a fixed time period. We train an algorithm that predicts the number of retweets during time T since the initial moment. In addition to a standard set of features we utilize several new ones. One of the most important features is the flow of the cascade. Another one is PageRank on the retweet graph, which can be considered as the measure of influence of users.

Language: English

Keywords: information diffusion

In book

CIKM '12: Proceedings of the 21st ACM international conference on Information and knowledge management

NY: ACM, 2012.

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Information diffusion on social networks has many potential real-world applications such as online marketing, e-government campaigns, and predicting large social events. Modeling information diffusion is therefore a crucial task in order both to understand its diffusion mechanism and to better control it. Our research aims at finding what factors might influence people in adopting a ...

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Predicting the Audience Size of a Tweet

Kupavskii A., Umnov A., Gusev G. et al., , in: Proceedings of the 7th International AAAI Conference on Weblogs and Social Media.: United States of America: AAAI Press, 2013. P. 693–696.

We study information dissemination in Twitter. We present an analysis of two important characteristics of so called “ retweet cascades”: retweet count and “show” count, i.e., number of users that receive the tweet in their feed. We show that these two measures behave differently. We describe three models that are aimed to predict the audience ...

Added: March 2, 2015