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Community Detection and Probability Estimation of Community Connectedness


Affiliations
1 CSE Department, RCC Institute of Information Technology, Kolkata - 700015, West Bengal, India
 

We present a methodology to analyze large social data sets based on a new community detection algorithm and based on the communities we find a method to detect the probability of a node to be part of a community. Our main aim is to find the communities based on locally computed score and later fit the scores in a distribution to find the probability of its connectedness in a community. Our work is mostly based on FOCS algorithm. Therefore in this article we refer to the FOCS algorithm often, describe it and then point out the changes brought by us.

Keywords

Community Connectedness, Probability Estimation, Social Network Analysis.
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  • Community Detection and Probability Estimation of Community Connectedness

Abstract Views: 762  |  PDF Views: 347

Authors

Ranabir Devgupta
CSE Department, RCC Institute of Information Technology, Kolkata - 700015, West Bengal, India
Arka Prava Bandyopadhyay
CSE Department, RCC Institute of Information Technology, Kolkata - 700015, West Bengal, India

Abstract


We present a methodology to analyze large social data sets based on a new community detection algorithm and based on the communities we find a method to detect the probability of a node to be part of a community. Our main aim is to find the communities based on locally computed score and later fit the scores in a distribution to find the probability of its connectedness in a community. Our work is mostly based on FOCS algorithm. Therefore in this article we refer to the FOCS algorithm often, describe it and then point out the changes brought by us.

Keywords


Community Connectedness, Probability Estimation, Social Network Analysis.

References