Abstract: Evaluating the scientific value of publications has always been a research focus in the field of bibliometrics.However,some mainstream methods based on data mining overlook the influence of malicious activities and result in poor evaluation results.To solve this problem,this paper proposed a new method named ReputeRank,which employs a creditworthiness mechanism to evaluate the effectiveness of publications in the citation network.The creditworthiness mechanism consists of the seeds selection phase,the spread credit phase and the integrated computation phase.First,ReputeRank employs background information on the division of SCI Periodicals to select potential good seeds and bad seeds in the citation network.Then,in light of assumption that good credibility seeds pointing to papers which usually have a higher credible degree while bad credibility seeds pointing to papers which often have a lower credible degree,the method uses TrustRank and Anti-TrustRank evaluation formula to iteratively spread trust values and distrust values over the citation network.Finally,according to the trust and distrust values in the citation network,the method utilizes an integrated equation to comprehensively compute the score value of each paper and arranges all papers in the descen-ding order of the score values.The experimental results on KDD cup 2003 datasets demonstrate that ReputeRank has good performance of effectiveness and robustness compared with PageRank,CountDegree and SPRank.

Key words: Citation network, Credibility, Evaluation of academic influence, Information dissemination