Abstract:

We propose documentbased ACA (DACA) which utilizes the co-citation counts of the same pair of authors’ articles as the inputs of raw co-citation matrix to reconstruct it. Besides, we improve the method of calculating citations published time with the hypothesis that papers published in a short time are likely to be ignored because of its relatively low citations. This paper puts citations published time and documentbased co-citation into traditional ACA, namely documentand timebased ACA (DTACA). Network visualization and MDS-measurement are then employed. The results show that the proposed DTACA method can mine more details in authors’ clustering and can thus improve the performance and the accuracy of knowledge domain mapping, compared to traditional ACA.

Key words: Author Co-citation analysis, Co-citation analysis, Citation analysis, Informetrics