Analyzing the influential people in Sina Weibo dataset
- 1 December 2013
- conference paper
- conference paper
- Published by Institute of Electrical and Electronics Engineers (IEEE) in 2013 IEEE Global Communications Conference (GLOBECOM)
- No. 1930529X,p. 3066-3071
- https://doi.org/10.1109/glocom.2013.6831542
Abstract
With the increasingly rapid growth of micro-blogging services, influence analysis is becoming a very important topic in this area. Sina Weibo, one of the largest mirco-blogging services in China, has provided a new operation comment-only, which allows users to give feedback on a post without forwarding. However, most of existing works focus on Twitter, which fail to consider this new operation. In paper, we propose a new influence measurement method called WeiboRank on Sina Weibo which applies comment-only operation to help researchers to find ignored influential users who have big influential in comment dimension. Furthermore we analyze why a particular user is influential based on tracing the source of influence to find out which aspects contribute to influence. Our experiments based on a subset of a whole Sina Weibo datatset, which includes three-month records of 22,514,394 users. We conduct extensive experiments and results show that we can accurately find the most influential individuals among entire social networks, while the running time of the algorithm increases linearly with any increase in data size, which is suitable for large scale networks.Keywords
This publication has 10 references indexed in Scilit:
- Utilizing Social Influence in Content Distribution NetworksPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2011
- Relationship classification in large scale online social networks and its impact on information propagationPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2011
- Everyone's an influencerPublished by Association for Computing Machinery (ACM) ,2011
- Measuring User Influence in Twitter: The Million Follower FallacyProceedings of the International AAAI Conference on Web and Social Media, 2010
- What is Twitter, a social network or a news media?Published by Association for Computing Machinery (ACM) ,2010
- TwitterRankPublished by Association for Computing Machinery (ACM) ,2010
- Social influence analysis in large-scale networksPublished by Association for Computing Machinery (ACM) ,2009
- Identifying the influential bloggers in a communityPublished by Association for Computing Machinery (ACM) ,2008
- Progressive skyline computation in database systemsACM Transactions on Database Systems, 2005
- Topic-sensitive pagerank: A context-sensitive ranking algorithm for web searchIEEE Transactions on Knowledge and Data Engineering, 2003