Bin Tareaf, Raad; Berger, Philipp; Hennig, Patrick; Koall, Sebastian; Kohstall, Jan; Meinel, Christoph
International Conference on Algorithms, Computing and Systems
Jeju Island, South Korea
ACM & Journal of Computer (ISSN: 1796-203X)
International Conference on Algorithms, Computing and Systems (ICACS 2017)
In this paper, we present our experiences in analyzing Twitter data. The analysis has shown that information diffuses over time through the Twitter network in certain patterns. Furthermore, it has shown those friend relationships significantly influence the information propagation speed on Twitter. Since it was launched in 2006, the microblogging service grew tremendously. Tweets are sent by users all around the world. Results show that there are two major patterns. While these patterns accommodate us to understand the diffusion of information through Twitter in an even better plan, the analysis of friend networks provides information on who influences the network, concerning the number of re-tweets and the time between a tweet and its re-tweets. The approaches have been evaluated both technically, based on how certain a topic matches one of the patterns and how prominent friends are compared to other users, and conceptually, based on existing, well-known approaches in measuring the speed and scale of information diffusion on Twitter.