Analyzing the Influence of Academic Papers Based on Improved PageRank The number of papers, published in different fields, is continually increasing, but the quality of papers varies widely. Scholars evaluate the quality and influence of a paper by the number of times the paper was cited, but the result of this citation quantity method is not accurate enough especially for new papers. Our society needs an accurate, objective and fair evaluation of papers. To address these problems, this article presents a method for evaluating the impact of papers. We analyze the influence of each academic paper in the citation network based on the improved PageRank algorithm and combined with the personal influence of the authors and the published date. Thus, this method tends to select highquality authors and highquality citations as highimpact papers. The comparison results showed that our method outperformed the traditional method of citation number and PageRank algorithm.

IIRank: A Novel Algorithm for Identifying Influencers in MicroBlog Social Networks In this paper, we analyze the influence of microblogger and put forward new concepts of sources, such as the positive microblog source, the negative microblog source, and the neutral source in microblog field based on the concepts of sources in electromagnetic field theory. Then, we propose a novel Individual Influence Ranking algorithm called IIRank. IIRank first calculates the microblog flux by the way of calculating the magnetic flux to assess usersu0027 behaviors. It then calculates the microblog flux density with the microblog flux to rank the microbloggeru0027s influence. We have implemented the algorithm to handle the realworld Sina Weibo data. Experimental results show that the proposed method significantly improves the assessment preciseness over the popular and famous PageRank algorithm.