• Dr M VENU GOPALACHARI
• P Hima Bindu

Social Networks became popular in recent times with the applications such as facebook, twitter, wechat etc, which provides a platform to share wide variety of information in turn involved in many business models like target marketing. Social influence analysis (SIA) is a vast research field on the social networks that includes topics such as community detection, influence maximization and minimization, flow of influence, and individual influence. This project focuses on influence maximization problem, which is to select a subset of nodes, so that the spread of information could be maximized. However, the existing works were more focused to define influence propagation but did not consider the size of the influence node set. The size of the influence node set matters if it overlaps neighbor node set. Also the existing works considered positive influence dominant set while the negative influence is ignored. This paper developed a methodology that detects minimum sized maximum influential nodes in social network which also considers the percentages of positive and negative influences of the users in the community.

Social Networks, Influential Node set, Minimum Influential Node, Greedy algorithm

"Minimal Influential Node Set Detection in Social Networks", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.8, Issue 6, page no.c680-c682, June-2021, Available :http://www.jetir.org/papers/JETIR2106364.pdf

"Minimal Influential Node Set Detection in Social Networks", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.8, Issue 6, page no. ppc680-c682, June-2021, Available at : http://www.jetir.org/papers/JETIR2106364.pdf