关键词: 情感分析, 社交网络, 影响最大化

Abstract: Influence maximization is a problem of finding a subset of nodes in a social network, which can maximize the influence spread. Most existing influence maximization algorithms merely rely on the social graph. This paper proposes a new sentiment influence model, named sentiment influence distribution (SID) model. SID model simultaneously utilizes the social graph, user interaction data and sentiment of microblog posts. The paper demonstrates
that the sentiment influence maximization problem is an NP-hard problem under the SID model and the sentiment influence function is monotone and submodular. It also develops an approximate algorithm which can provide high performance guarantee. Experimental results from real data show the effectiveness of the proposed SID model compared to the traditional IC model and LT model.

Key words: sentiment analysis, social networks, influence maximization