Analyzing the Impact of Information Diffusion Models on Social Networks

Abstract

Today, personal life has been induced by online informal communities all over the world with the increase of social networks. They expect to move more personal information to online communities. Hence, online social systems can mirror the structure of human culture. A snippet of data can be traded or diffused between people in informal communities. From this dissemination procedure, bunches of dormant data can be mined. It very well may be utilized for showcase anticipating, gossip controlling, and sentiment checking in addition to other things. Nonetheless, the exploration of these applications relies upon the dispersion models furthermore, techniques. Hence, we review different data dissemination models from late decades. From an examination procedure see, we isolate the dispersion models into two classes—informative models and prescient models—in which the previous incorporates plagues and impact models and the last incorporates free course, direct limit, and game hypothesis models. The motivation behind this paper is to explore the examination strategies and methods, and contrast them agreeing with the above classes. The entire examination structure of the data dissemination models dependent on our view is given. There is a discussion towards the each segment, enumerating related models that are referenced in the writing. We presume that these two models are not autonomous, they generally supplement each other. At long last, the issues of the informal organizations research are analyzed, and future investigations are proposed. In this paper we proposed Profile Based Equal Responsibility Rumor Diffusion Game Model (PERRDGM) which is compared with Equal Responsibility Rumor Diffusion Game Model (ERRDGM) and we observed that cover degree is improved by 6% and precision by 1% using proposed model.