Discovery of Really Popular Friends from Social Networks

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

Big Data and Cloud Computing（2014）

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摘要

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.

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关键词

social computing and its applications,social networking technologies,knowledge sharing,social computing,social media data,behavioural sciences computing,social computing and networking,social networking software,data mining,social network analysis and mining,social conventions,social behaviour,social networking (online),social networking sites,popular friends,social contexts,upper bound,databases

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