On modeling virality of twitter content

Authors:
Tuan-Anh Hoang;Ee-Peng Lim;Palakorn Achananuparp;Jing Jiang;Feida Zhu
Affiliations:
School of Information Systems, Singapore Management University;School of Information Systems, Singapore Management University;School of Information Systems, Singapore Management University;School of Information Systems, Singapore Management University;School of Information Systems, Singapore Management University
Venue:
ICADL'11 Proceedings of the 13th international conference on Asia-pacific digital libraries: for cultural heritage, knowledge dissemination, and future creation
Year:
2011

Citing 5
Cited 0

The dynamics of viral marketing

ACM Transactions on the Web (TWEB)
On Modularity Clustering

IEEE Transactions on Knowledge and Data Engineering
Introduction to Information Retrieval

Introduction to Information Retrieval
TwitterRank: finding topic-sensitive influential twitterers

Proceedings of the third ACM international conference on Web search and data mining
The Meme Ranking Problem: Maximizing Microblogging Virality

ICDMW '10 Proceedings of the 2010 IEEE International Conference on Data Mining Workshops

Quantified Score

Hi-index	0.00

Visualization

Abstract

Twitter is a popular microblogging site where users can easily use mobile phones or desktop machines to generate short messages to be shared with others in realtime. Twitter has seen heavy usage in many recent international events including Japan earthquake, Iran election, etc. In such events, many tweets may become viral for different reasons. In this paper, we study the virality of socio-political tweet content in the Singapore's 2011 general election (GE2011). We collected tweet data generated by about 20K Singapore users from 1 April 2011 till 12 May 2011, and the follow relationships among them. We introduce several quantitative indices for measuring the virality of tweets that are retweeted. Using these indices, we identify the most viral messages in GE2011 as well as the users behind them.