关键词: 作者共被引分析, 引文邻近位置, 聚类分析, 可视化, 引文分析, 学术评价

Abstract: In the co-citation analysis, the distance cited by the co-cited authors in the citing literature has a certain influence on the relationship strength between authors. In order to explore this kind of influence relationship and improve the lack of position information in the author co-citation analysis, this paper adds the position information cited by the author in the citing literature to the author co-citation analysis. The analysis method is called "the author co-citation analysis based on references proximity position（RP-ACA）". The papers were sampled five CSSCI journals in the field of Information Science in 2008-2017. 37 core authors were identified to constructing ACA matrix and RP-ACA matrix, then Ucinet was used for network density analysis, and VOSviewer was used for clustering. By comparing the clustering effect and keywords analysis, it is found that compared with the traditional ACA method, the RP-ACA method is more accurate and detailed in identifying the author's research direction and dividing the author group.

Key words: Author co-citation analysis, References proximity position, Cluster analysis, Visualization, Citation evaluation, Academic evaluation