Searching for and Ranking Alpha Users in Massive Telecom Social Networks with MapReduce

• Main Authors: Tsai, Sheng-Wen, 蔡勝文
• Other Authors: Gau, Rung-Hung
• Format: Others
• Language: en_US
• Published: 2013
• Online Access: http://ndltd.ncl.edu.tw/handle/11061699860640748477

碩士 === 國立交通大學 === 電信工程研究所 === 101 === In this thesis, we propose novel MapReduce algorithms to search for and rank alpha users in massive telecom social networks. We first apply the principle of divide-and-conquer to find out trusses in a social graph and then use the eigenvector centrality to identify alpha users in the trusses in parallel. In addition, we propose ranking alpha users in distinct trusses based on their shortest path coverage. Furthermore, we propose novel algorithms to efficiently detect and decompose giant components in a social graph. In addition to synthetic social networks, we have used the proposed algorithms to analyze real smart phone social networks that are created based on call detail records collected by a telecom operator.