Discovery of Really Popular Friends from Social Networks

Author

Fan Jiang ; Leung, Carson Kai-Sang ; Dacheng Liu ; Peddle, Aaron M.

Author_Institution

Dept. of Comput. Sci., Univ. of Manitoba, Winnipeg, MB, Canada

fYear

2014

fDate

3-5 Dec. 2014

Firstpage

342

Lastpage

349

Abstract

Advances in social computing and networking software and technologies enable users to intersect social behaviour with computing systems for creating social conventions and contexts. In recent years, social networking sites have become popular to facilitate collaboration and knowledge sharing between users. A rich set of information is embedded in these social media data. In this paper, we propose algorithms that incorporate both connectivity and frequency information in helping users to discover really popular friends from social networks. Experimental results show the effectiveness of our algorithms in the discovery of really popular friends from social networks.

Keywords

behavioural sciences computing; data mining; social networking (online); knowledge sharing; social behaviour; social computing; social contexts; social conventions; social media data; social networking sites; social networking software; social networking technologies; Data mining; Databases; Equations; Facebook; Social computing; Upper bound; Social computing and networking; data mining; popular friends; social computing and its applications; social network analysis and mining;

fLanguage

English

Publisher

ieee

Conference_Titel

Big Data and Cloud Computing (BdCloud), 2014 IEEE Fourth International Conference on

Conference_Location

Sydney, NSW

Type

conf

DOI

10.1109/BDCloud.2014.110

Filename

7034814