Analysis on information spreading as recorded in twittersphere

Abstract

Twitter is offering an unprecedented opportunity for the study of information spreading in human society as all actions and underlying social network can be recorded. In this thesis, we present empirical study of information spreading phenomena in Twitter. We collected 32 million photo URLs posted on Twitter via Twitpic and related 52 million tweets from April 2010 to June 2010. Twitpic links guarantee that the source of information is unique and a Twitter user. Thus, Twitpic links eliminate chance of having multiple source users who bring the same information to Twittersphere. We show analysis on information creation and spreading tracking Twitpic URL links. Microscopic characteristics of information diffusion at the individual information level are not well-explored yet. We analyze temporal and topological characteristics of microscopic information spreading characteristics with the reconstructed diffusion trees of Korean users. We discover that diffusion in Twitter is very fast making wide and shallow diffusion trees. We show information diffusion model which is an extension of Independent Cascade Model considering response time of users. We show that spreading probabilities are infuenced by type of information and directness to the original source. To be best of our knowledge this work is the first study on characteristics of microscopic information diffusion in Twitter.