Bonded-communities in HantaVirus research: a research collaboration network (RCN) analysis

Hantavirus, one of the deadliest viruses known to humans, hospitalizes tens of thousands of people each year in Asia, Europe and the Americas. Transmitted by infected rodents and their excreta, Hantavirus are identified as etiologic agents of two main types of diseases—Hemorrhagic fever with renal syndrome and hantavirus pulmonary syndrome, the latter having a fatality rate of above 40 %. Although considerable research for over two decades has been going on in this area, bibliometric studies to gauge the state of research of this field have been rare. An analysis of 2631 articles, extracted from WoS databases on Hantavirus between 1980 and 2014, indicated a progressive increase (R (2) = 0.93) in the number of papers over the years, with the majority of papers being published in the USA and Europe. About 95 % papers were co-authored and the most common arrangement was 4–6 authors per paper. Co-authorship has seen a steady increase (R (2) = 0.57) over the years. We apply research collaboration network analysis to investigate the best-connected authors in the field. The author-based networks have 49 components (connected clump of nodes) with 7373 vertices (authors) and 49,747 edges (co-author associations) between them. The giant component (the largest component) is healthy, occupying 84.19 % or 6208 vertices with 47,117 edges between them. By using edge-weight threshold, we drill down into the network to reveal bonded communities. We find three communities’ hotspots—one, led by researchers at University of Helsinki, Finland; a second, led by the Centers of Disease Control and Prevention, USA; and a third, led by Hokkaido University, Japan. Significant correlation was found between author’s structural position in the network and research performance, thus further supporting a well-studied phenomenon that centrality effects research productivity. However, it was the PageRank centrality that out-performed degree and betweenness centrality in its strength of correlation with research performance.