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Identifying Opinion Leader in the Internet Forum
Chao Wu,Chunlin Li,Wei Yan,Youlong Luo,Xijun Mao,Shumeng Du,Mingming Li 보안공학연구지원센터 2015 International Journal of Hybrid Information Techno Vol.8 No.11
Opinion leader is an authority person who has great influence in BBS. Their linguistic behavior has a huge impact on net citizen’s behavior and thought. In this paper, we propose an algorithm called OLRA (Opinion Leader PageRank Algorithm) based on topic-field to identify opinion leaders in the Internet forum. In the algorithm the closeness degree factor and sentiment analyses are taken into consideration. Meanwhile, these two authority values are defined as the weight of links among users. The data is collected from a number of posts on Tianya forum which is a famous forum in China. In the experiment, the algorithm is compared with Interest-based PageRank algorithm, online time Algorithm, and Experience-based Algorithm, the result shows that the OLRA algorithm can identify opinion leaders than others in the Internet forum effectively.
Entity Relationship Modeling Approach Based on Micro- Blog Tag
Junjiang Li,Chunlin Li,Youlong Luo,Yahui Zhao,Xijun Mao 보안공학연구지원센터 2015 International Journal of Multimedia and Ubiquitous Vol.10 No.7
Due to the huge information, short length and noise data, the traditional method has poor effect on micro-blog entity relationship modeling. In this paper, a new micro-blog user interests discovering approach based on tag is presented to improve the entity relationship modeling. First the matrix of user tag built by traditional way may generate the problem of sparse matrix in tag recommendation, so we introduce the information of micro-blog and establish the bipartite graph of User-Tag and Tag-Word respectively, then use them to recommend tag to micro-blog users. Meanwhile interactive relationship between users also show their interests, we establish a graph of tag relation by users’ relationship and propose a method called Tag Rank on the basis of this graph to improve the precision of the model. Finally, we combine the two methods to discover user interests. In the experiment, we use several measurement metrics: F-value, precision and the recall rate. It is proven that the new approach in the paper have a perfect performance.