• D.SWETHA
• Dr. A.M.VISHWABHARATHY
• Dr.M.SUJATHA

Social influence and influence diffusion has been widely studied in online social networks. However, most existing works on influence diffusion focus on static networks. In this paper, we study the problem of maximizing influence diffusion in a dynamic social network. Specifically, the network changes over time and the changes can be only observed by periodically probing some nodes for the update of their connections. Our goal then is to probe a subset of nodes in a social network so that the actual influence diffusion process in the network can be best uncovered with the probing nodes. We propose a novel algorithm to approximate the optimal solution. The algorithm, through probing a small portion of the network, minimizes the possible error between the observed network and the real network. We introduce a generic model, called TBaSIC, and describe how to estimate its parameters from users behaviours using machine learning techniques. Contrary to classical approaches where the parameters are fixed in advance, T-BaSIC ’s parameters are functions depending of time, which permit to better approximate and adapt to the diffusion phenomenon observed in online social networks. Our proposal has been validated on real Twitter datasets. Experiments show that our approach is able to capture the particular patterns of diffusion depending of the studied sub networks of users and topics. The results corroborate the “two-step” theory (1955) that states that information flows from media to a few “opinion leaders” who then transfer it to the mass population via social networks and show that it applies in the online context. This work also highlights interesting recommendations for future investigations.

Social networks, influence maximization, predictive models. , heuristic algorithms.

"EFFICIENT INFLUENCE MAXIMIZATION IN SOCIAL NETWORKS FOR TEMPORAL DYNAMIC PREDICTION", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.5, Issue 8, page no.261-266, August-2018, Available :http://www.jetir.org/papers/JETIR1808036.pdf

"EFFICIENT INFLUENCE MAXIMIZATION IN SOCIAL NETWORKS FOR TEMPORAL DYNAMIC PREDICTION", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.5, Issue 8, page no. pp261-266, August-2018, Available at : http://www.jetir.org/papers/JETIR1808036.pdf