The Characteristic Model of Information Diffusion in Online Social Networks, The Case of Twitter in Pakistan

Abstract

Online social networks have become a part of billions of peoples’ daily lives. Through their interactions on such networks, these people come across a wide variety of information. Achieving a better understanding of how particular information propagates and diffuses through these networks is important to more accurately understand people and their interaction with information. Twitter is an extremely popular online social network that deals with a lot of information every day, including information regarding particular people, events, organizations, situations, interest groups, etc. The diffusion of such data depends on multiple factors and there has been much research into finding out the intricacies of how information travels through online social networks, especially Twitter. While there has been a lot of work done to understand information diffusion in Twitter, very little of it focuses Twitter in the Pakistani context. The users of social networks in Pakistan could be potentially very different when compared to other communities. This research attempts to delve into this phenomenon deeper and study information diffusion in Twitter in Pakistan, focusing more specifically on the characteristics that enable a particular tweet to be retweeted more than others. A dataset of trending Pakistani tweets is taken over a period of 3 months using the Twitter API. Various user, content and time-based characteristics are defined and the correlation for each of these characteristics to the retweet count is calculated using multiple correlation algorithms as well as a trained neural network to find out which characteristic of a tweet has what affect on its potential to diffuse further into the network.