Abstract

In co-authorship networks, temporal networks can be modeled by identifying the formation and dissolution (linking and removing) of co-authorship relationships over time from the publication year information of the papers. Therefore, this study seeks to analyze the overall research collaboration networks of data papers and articles from an evolutionary perspective for modeling the temporal network in terms of informetrics and investigating the dynamic and structural mechanisms of the temporal co-authorship network. For that purpose, Biodiversity Data Journal, a mixed data journal in the biodiversity domain was used as the unit of analysis in this study as this domain had proposed data paper as a new mechanism for data publication. In addition, bibliometric records of 247 data papers and 638 articles involving two or more researchers were collected from the Web of Science. The results indicated that the dynamic co-authorship networks of data papers and articles in the biodiversity domain exhibited the scale-free property of a complex network and the small-world property in the Watts-Strogatz sense during the network evolution. Also, both publication types kept the structure of locally cohesive author groups over time in the networks. The implementation of TTBC (Temporal Triadic Betweenness Centrality) has allowed for the examination and tracking of the evolutionary trends of important or influential time-dependent authors (nodes) by the target year. And last, visualization with a dynamic approach enabled a more effective identification of analysis results, such as the exhibited structural difference in the temporal co-authorship networks of data papers and articles in the biodiversity domain, which can be interpreted as the structural properties of the networks among collaborative researchers dealing with data.