|Title:||A method for community recommendation for social networks|
Alcaraz Calero J.M.
|Published in:||Proceedings of 2015 International Conference on Advances in Computing, Communications and Informatics, ICACCI 2015|
|Abstract:||The increasing use of social networks has been beneficial in our daily lives. In this paper we consider the problem of recommending a user centric community based on a user's interest topic, location, and relationship network. Our framework can address some significant socio-psychological issues and also allows to understand information propagation. We consider a user's network structure to calculate the proximity between any two users. We suggest a community recommendation procedure that recommends only the users who are interested in socialization based on several features of a user profile. The recommendation set prunes out bots and cyborgs and it consists of human users only. We have used several properties to analyze a user. We have shown that these properties can be leveraged to improve the performance of the approach in online social networks. We have conducted several experiments using Twitter data. The experimental results illustrate the effectiveness of our approach. © 2015 IEEE.|
|Citation:||Proceedings of 2015 International Conference on Advances in Computing, Communications and Informatics, ICACCI 2015, (2015), 2341- 2347|
|Publisher:||Institute of Electrical and Electronics Engineers Inc.|
|Author Scopus IDs:||57212204992|
|Author Affiliations:||Banerjee, S., Department of Computer Science and Engineering, Indian Institute of Technology Roorkee247667, India|
Niyogi, R., Department of Computer Science and Engineering, Indian Institute of Technology Roorkee247667, India
|Appears in Collections:||Conference Publications [CS]|
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