Abstract

This study aims to validate whether the research performance of scholars correlates with how the scholars work together. Although the most straightforward approaches are centrality measurements or community detection, scholars mostly participate in multiple research groups and have different roles in each group. Thus, we concentrate on the subgraphs of co-authorship networks rooted in each scholar that cover (i) overlapping of the research groups on the scholar and (ii) roles of the scholar in the groups. This study calls the subgraphs “collaboration patterns” and applies subgraph embedding methods to discover and represent the collaboration patterns. Based on embedding the collaboration patterns, we have clustered scholars according to their collaboration styles. Then, we have examined whether scholars in each cluster have similar research performance, using the quantitative indicators. The coherence of the indicators cannot be solid proofs for validating the correlation between collaboration and performance. Nevertheless, the examination for clusters has exhibited that the collaboration patterns can reflect research styles of scholars. This information will enable us to predict the research performance more accurately since the research styles are more consistent and sustainable features of scholars than a few high-impact publications.

Highlights

  • As academic societies are getting broader and more subdivided, various intelligent services for scholars have been required

  • We have attempted to validate the correlation between the performance of scholars and the research collaboration patterns of scholars

  • We clustered the scholars according to vector representations of their collaboration patterns

Read more

Summary

Introduction

As academic societies are getting broader and more subdivided, various intelligent services for scholars have been required (e.g., a recommendation for collaborators, research topics, or journals). For those services, measurements for evaluating performance of scholars, quality of journals, or prominence of research topics are essential and fundamental components. There have been various studies for defining quantitative indicators to evaluate and compare entities in the academia (Hirsch, 2005, 2010; Sidiropoulos et al, 2007; Wu, 2010; Galam, 2011) These indicators have mostly employed (i) count-based and (ii) network-based approaches. Even if two scholars have the same number of citations, we cannot answer whether the two scholars have similar research performance

Objectives
Results
Conclusion
Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call