Publication Type
Conference Proceeding Article
Version
acceptedVersion
Publication Date
10-2011
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.
Keywords
General Elections, Microblogging, Quantitative indices, Real time, Short message, Singapore
Discipline
Asian Studies | Databases and Information Systems | Numerical Analysis and Scientific Computing | Social Media
Research Areas
Data Science and Engineering
Publication
Digital Libraries: 13th International Conference on Asia-Pacific Digital Libraries, ICADL 2011, Beijing, China, October 24-27: Proceedings
Volume
7008
First Page
212
Last Page
221
ISBN
9783642248269
Identifier
10.1007/978-3-642-24826-9_27
Publisher
Springer
City or Country
Heidelberg
Citation
HOANG, Tuan Anh; LIM, Ee Peng; ACHANANUPARP, Palakorn; JIANG, Jing; and ZHU, Feida.
On Modeling Virality of Twitter Content. (2011). Digital Libraries: 13th International Conference on Asia-Pacific Digital Libraries, ICADL 2011, Beijing, China, October 24-27: Proceedings. 7008, 212-221.
Available at: https://ink.library.smu.edu.sg/sis_research/1440
Copyright Owner and License
LARC
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Additional URL
https://doi.org/10.1007/978-3-642-24826-9_27
Included in
Asian Studies Commons, Databases and Information Systems Commons, Numerical Analysis and Scientific Computing Commons, Social Media Commons
Comments
We would like to acknowledge that this research was carried out at the Living Analytics Research Centre (LARC), sponsored by Singapore National Research Foundation and Interactive & Digital Media Programme Office, Media Development Authority.