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论文类型：会议论文

发表时间：2014-01-01

收录刊物：CPCI-S

页面范围：1197-1202

关键字：research community; article level metrics; citation; social bookmark

摘要：With the rapid increase of research papers, article-level metrics are of growing importance for helping researchers select papers. Classical metrics have a significant drawback of just using single factor, which limits the effectiveness of assessing papers in different periods after publication. Moreover, with the development of web 2.0, some new factors are introduced to assess papers. So, a novel article level metric in the context of research community (ALM_RC) is proposed. It integrates the impact of different factors comprehensively, because different factors have different time features and can complement each other in different periods after publication. In addition, as a research community is based on certain research directions, it is a relatively stable environment with related journals and scholars contributing their efforts to development of this research field. So in the context of research community, it is consistent, practical and reasonable to calculate the impact of the journals and scholars under relatively fair criteria. Experimental results show the novel metric is effective and robust in assessing papers.