In this study, the structure of co-authorship networks was analyzed using the Macro-level and Micro-level Approach. The study also examined the relationship between centrality measures and citation performance.
The research reported here favors a bibliometric approach aiming to visualize the co-authorship networks building on the network analysis method. The population of the research consisted of 24308 authors of the indexed papers in the WOS database. To collect the data pertaining to the citation performance of a given researcher, the articles the given researchers published in a period of three years were taken into account. The citation data (excluding the self-citation) of a given article were gathered considering a three-year lapse after its publication.  The results suggested that the mean of co-authorship for each article was 2.8 authors and the ratio of co-authored articles to single-authored was 89.4%. Also, this said co-authorship network was a network of “small world” and lacked “scale”. The achieved findings illustrated that any increase in the rate of centrality and betweenness centrality of articles led to an increase in the amount of received citations. That said, no significant relationship was found between closeness centrality and the amount of received citations in this area. In this period, the variable of closeness centrality was able to predict the significance for the citation performance of the researchers with Beta coefficient of 0.289 (p> 0.000). Therefore, it is safe to say that researchers’ citations performance was affected by betweenness centrality measures and this measure played a pivotal role in the researchers’ citation performance at this period of time. Although in a co-authoring network occupying a central position by the researcher, it is of strategic importance in terms of its proximity but it does not necessarily improve his performance. A definitive commentary on the relation between interstitial centrality and citation performance, more research is needed.
Keywords: Research Impact, Citation Performance, Centrality Measures, Macro-level Approach, Micro-level Approach, Co-authorship < span dir="RTL">