Open Access. Powered by Scholars. Published by Universities.®

Computer Sciences Commons

Open Access. Powered by Scholars. Published by Universities.®

Numerical Analysis and Scientific Computing

2011

Twitter

Articles 1 - 2 of 2

Full-Text Articles in Computer Sciences

Fragile Online Relationship: A First Look At Unfollow Dynamics In Twitter, Haewoon Kwak, Hyunwoo Chun, Sue. Moon May 2011

Fragile Online Relationship: A First Look At Unfollow Dynamics In Twitter, Haewoon Kwak, Hyunwoo Chun, Sue. Moon

Research Collection School Of Computing and Information Systems

We analyze the dynamics of the behavior known as 'unfollow' in Twitter. We collected daily snapshots of the online relationships of 1.2 million Korean-speaking users for 51 days as well as all of their tweets. We found that Twitter users frequently unfollow. We then discover the major factors, including the reciprocity of the relationships, the duration of a relationship, the followees' informativeness, and the overlap of the relationships, which affect the decision to unfollow. We conduct interview with 22 Korean respondents to supplement the quantitative results.They unfollowed those who left many tweets within a short time, created tweets about uninteresting …


Comparing Twitter And Traditional Media Using Topic Models, Wayne Xin Zhao, Jing Jiang, Jianshu Weng, Jing He, Ee Peng Lim, Hongfei Yan, Xiaoming Li Apr 2011

Comparing Twitter And Traditional Media Using Topic Models, Wayne Xin Zhao, Jing Jiang, Jianshu Weng, Jing He, Ee Peng Lim, Hongfei Yan, Xiaoming Li

Research Collection School Of Computing and Information Systems

Twitter as a new form of social media can potentially contain much useful information, but content analysis on Twitter has not been well studied. In particular, it is not clear whether as an information source Twitter can be simply regarded as a faster news feed that covers mostly the same information as traditional news media. In This paper we empirically compare the content of Twitter with a traditional news medium, New York Times, using unsupervised topic modeling. We use a Twitter-LDA model to discover topics from a representative sample of the entire Twitter. We then use text mining techniques to …