Recommender System with Machine Learning and Artificial Intelligence

21Influenceable Targets Recommendation Analyzing Social Activities in Egocentric Online Social Networks

Soumyadeep Debnath¹, Dhrubasish Sarkar²* and Dipankar Das³

¹ Tata Consultancy Services Limited, Kolkata, India

² Amity Institute of Information Technology (AIIT), Amity University, Kolkata, India

³ Department of Computer Science and Engineering, Jadavpur University, Kolkata, India

Abstract

Nowadays, Online Social Media (OSM) has vast impact on various aspects of industry, business and society along with on user’s life. In an OSN platform, reaching the target users is one of the primary focus for most of the businesses and other organizations. Identification and recommendation of influenceable targets helps to capture the appropriate audience efficiently and effectively. In this paper, an effective model has been discussed in egocentric OSN by incorporating an efficient influence measured Recommendation System in order to generate a list of top most influenceable target users among all connected network members for any specific social network user. Firstly the list of interacted network members has been updated based on all activities. On which the interacted network members with most similar activities have been recommended based on the specific influence category with sentiment type. After that the top most influenceable network members in basis of the required amount among those updated list of interacted network members have been identified with proper ranking by analyzing ...