Title
Prediction of retweet cascade size over time
Abstract
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.
Year
DOI
Venue
2012
10.1145/2396761.2398634
CIKM
Keywords
Field
DocType
great interest,retweet cascade,retweet cascade size,important feature,social media,current trend,future popularity,essential role,important online media,fixed time period,popular tweet
PageRank,Data mining,Graph,Viral marketing,Social media,Information retrieval,Computer science,sort,Popularity,Cascade,Digital media
Conference
Citations 
PageRank 
References 
27
1.11
7
Authors
7
Name
Order
Citations
PageRank
Andrey B. Kupavskii16422.31
Liudmila Ostroumova2475.00
Alexey Umnov3412.36
Svyatoslav Usachev4271.11
Pavel Serdyukov5134190.10
Gleb Gusev619016.53
Andrey Kustarev7312.26