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http://dx.doi.org/10.6109/jkiice.2015.19.6.1380

Relationship Between Tweet Frequency and User Velocity on Twitter  

Jeon, So-Young (Department of Applied Computer Engineering, Dankook University)
Lee, Al-Chan (Department of Mobile Systems Engineering, Dankook University)
Seo, Go-Eun (Department of Mobile Systems Engineering, Dankook University)
Shin, Won-Yong (Department of Computer Science and Engineering, Dankook University)
Publication Information
Journal of the Korea Institute of Information and Communication Engineering / v.19, no.6, 2015 , pp. 1380-1386 More about this Journal
Abstract
Recently, the importance of users' geographic location information has been highlighted with a rapid increase of online social network services. In this paper, by utilizing geo-tagged tweets that provides high-precision location information of users, we first identify both Twitter users' exact location and the corresponding timestamp when the tweet was sent. Then, we analyze a relationship between the tweet frequency and the average user velocity. Specifically, we introduce a tweet-frequency computing algorithm, and show analysis results by country and by city. As a main result, it is shown that the tweet frequency according to user velocity follows a power-law distribution (i.e., Zipf' distribution or a Pareto distribution). In addition, by performing a comparison between the United States and Japan, one can see that the exponent of the distribution in Japan is smaller than that in the United States.
Keywords
Geo-tagged tweet; user velocity; online social network; Twitter; tweet frequency;
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