Publication Type
Conference Proceeding Article
Version
publishedVersion
Publication Date
4-2010
Abstract
Twitter offers an explicit mechanism to facilitate information diffusion and has emerged as a new medium for communication. Many approaches to find influentials have been proposed, but they do not consider the temporal order of information adoption. In this work, we propose a novel method to find influentials by considering both the link structure and the temporal order of information adoption in Twitter. Our method finds distinct influentials who are not discovered by other methods.
Keywords
Social Networks, Twitter, Information Diffusion, Influentials, Ranking
Discipline
Numerical Analysis and Scientific Computing | Theory and Algorithms
Research Areas
Data Science and Engineering; Intelligent Systems and Optimization
Publication
Proceedings of the 19th International World Wide Web Conference, WWW 2010, Raleigh, NC, United States, April 26-30
First Page
1137
Last Page
1138
ISBN
978-1-60558-799-8
Identifier
10.1145/1772690.1772842
Publisher
ACM
City or Country
New York
Citation
1
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.