Analyzing Information Diffusion in Ego-centric Twitter Social Network

Abstract

The ever dynamic world of social network is progressively about innovation and this headway in advancements has been an amalgamation of several advantages and disadvantages. The most quickly developing segment of the web is the social media life. The simplicity of correspondence with the individuals living far with the rise of social media life is deserving of acclaim. These applications are presently even broadly utilized for advancing organizations or occasions. Speaking of social media, Twitter has emerged out to be the most influential social media platform. Therefore, it has common possibility to be the premise of future ego-centric networks and information exchange frameworks, notwithstanding novel types of internet administrations misusing the properties of human social connections. In this respect, our research focuses on study of information flow within ego-centric network with real data set extracted from Twitter user handle. Our proposed model performs high-level soft analysis via community detection techniques based on network homophily. This is followed by applying of various diffusion models to study information diffusion rate in ego network.