2010•RePEc: Research Papers in EconomicsRequires access

On the Correlation between Research Performance and Social Network Analysis Measures Applied to Research Collaboration Networks

Alireza Abbasi, Jörn Altmann

Open publisher page 7 citations

Abstract

In this study, we develop a theoretical model based on social network theory to understand how the collaboration (co-authorship) network of scholars correlates to the research performance of scholars. For this analysis, we use social network analysis (SNA) measures (i.e., normalized closeness centrality, normalized betweenness centrality, efficiency, and two types of degree centrality). The analysis of data shows that the research performance of scholars is positively correlated with two SNA measures (i.e., weighted degree centrality and efficiency). In particular, scholars with strong ties (i.e., repeated co-authorships, i.e., high weighted degree centrality) show a better research performance than those with low ties (e.g., single co-authorships with many different scholars). The results related to efficiency show that scholars, who maintain a strong co-authorship relationship to only one co-author of a group of linked co-authors (i.e., co-authors that have joined publications), perform better than those researchers with many relationships to the same group of linked co-authors.

Open-access reader

About this research paper

What this paper is about

In this study, we develop a theoretical model based on social network theory to understand how the collaboration (co-authorship) network of scholars correlates to the research performance of scholars. For this analysis, we use social network analysis (SNA) measures (i.e., normalized closeness centrality, normalized betweenness centrality, efficiency, and two types of degree centrality). The analysis of data shows that the research performance of scholars is positively correlated with two SNA measures (i.e., weighted degree centrality and efficiency). In particular, scholars with strong ties (i.e., repeated co-authorships, i.e., high weighted degree centrality) show a better research performance than those with low ties (e.g., single co-authorships with many different scholars). The results related to efficiency show that scholars, who maintain a strong co-authorship relationship to only one co-author of a group of linked co-authors (i.e., co-authors that have joined publications), perform better than those researchers with many relationships to the same group of linked co-authors.

Why it matters

OpenAlex reports 7 citations for this work. Citation counts describe recorded attention and do not establish research quality.

Key contribution

A contribution statement is not available in the OpenAlex record.

Method / approach

Method details are not available in the OpenAlex metadata.

Main findings

Findings are not separately available in the OpenAlex metadata.

Limitations

Limitations are not available in the OpenAlex metadata.

Applications

Application details are not available in the OpenAlex metadata.

Available abstract

In this study, we develop a theoretical model based on social network theory to understand how the collaboration (co-authorship) network of scholars correlates to the research performance of scholars. For this analysis, we use social network analysis (SNA) measures (i.e., normalized closeness centrality, normalized betweenness centrality, efficiency, and two types of degree centrality). The analysis of data shows that the research performance of scholars is positively correlated with two SNA measures (i.e., weighted degree centrality and efficiency). In particular, scholars with strong ties (i.e., repeated co-authorships, i.e., high weighted degree centrality) show a better research performance than those with low ties (e.g., single co-authorships with many different scholars). The results related to efficiency show that scholars, who maintain a strong co-authorship relationship to only one co-author of a group of linked co-authors (i.e., co-authors that have joined publications), perform better than those researchers with many relationships to the same group of linked co-authors.

Key concepts: Betweenness centrality, Centrality, Closeness, Social network analysis, Network analysis, Social network (sociolinguistics), Degree (music), Psychology

Related papers

Back to paper searchBrowse research topicsOriginal source