Network diffusion for information propagation in online social communities

Abstract

Analysis of online communities has pioneered extensive research initiatives towards impact of diffusion of information in online social network communities. There are various social analytical and mining techniques that assists in information propagation over online social networks. The main purpose behind diffusion is to spread the information in a social network in a less computational way which has been described in the proposed solution. For this purpose, our research involves community detection with centrality measures executed over nodes, i.e. social entities that assists in targeting advertising and anonymization over the social web. We detect communities from a social network using community detection algorithms, which is followed by identifying significant entities in those communities using centrality measures. This eventually helps to better track the spreading of information to maximum people in the connected network to promote better advertising of products or services, according to needs, preferences and search criteria.