Abstract: Opinion leader mining is an important topic of social network research which is of great significance in terms of internet public opinion control and information dissemination. LeaderRank is an effective opinion leader mining algorithm. This paper proposes a new algorithm based on LeaderRank with sentiment analysis and user’s liveness to identify the opinion leaders in comment network to achieve a better performance. Experiments based on SIR model show that both accuracy and anti-jamming capability of the proposed algorithm have been effectively improved.

Key words: social network, opinion leader mining, LeaderRank, sentiment analysis, user’s liveness

摘要： 意见领袖挖掘是社会网络研究的重要课题，对于舆情控制、信息传播等方面具有重要意义。LeaderRank算法是一个有效的意见领袖挖掘算法。为提高LeaderRank算法的准确性和抗干扰能力，在LeaderRank算法基础上，加入用户之间的情感倾向、用户活跃程度，提出了改进的LeaderRank算法。基于SIR模型的实验验证表明，改进算法的准确性和抗干扰能力均得到了有效提升。

关键词: 社会网络, 意见领袖挖掘, LeaderRank算法, 情感倾向, 用户活跃程度