Comparison of co-authorship networks across scientific fields using motifs

• Type: Article in International Conference Proceedings Book
• Date: 2012

Authors

Sarvenaz Choobdar (Author) Other; Pedro Ribeiro (Author) FCUP; Sylwia Bugla (Author) FCUP; Fernando Silva (Author) FCUP

Conference proceedings International

Title: 2012 IEEE/ACM INTERNATIONAL CONFERENCE ON ADVANCES IN SOCIAL NETWORKS ANALYSIS AND MINING (ASONAM)

Pages: 147-152

IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining

Kadir Has Univ, Istanbul, TURKEY, AUG 26-29, 2012

Indexing

ISI Web of Knowledge - 26 Citations

Scientific classification

FOS: Natural sciences > Computer and information sciences

Other information

Authenticus ID: P-005-720

DOI: 10.1109/asonam.2012.34

Abstract (EN): Comparing scientific production across different fields of knowledge is commonly controversial and subject to disagreement. Such comparisons are often based on quantitative indicators, such as papers per researcher, and data normalization is very difficult to accomplish. Different approaches can provide new insight and in this paper we focus on the comparison of different scientific fields based on their research collaboration networks. We use co-authorship networks where nodes are researchers and the edges show the existing co-authorship relations between them. Our comparison methodology is based on network motifs, which are over represented patterns, or subgraphs. We derive motif fingerprints for 22 scientific fields based on 29 different small motifs found in the corresponding co-authorship networks. These fingerprints provide a metric for assessing similarity among scientific fields, and our analysis shows that the discrimination power of the 29 motif types is not identical. We use a co-authorship dataset built from over 15,361 publications inducing a co-authorship network with over 32,842 researchers. Our results also show that we can group different fields according to their fingerprints, supporting the notion that some fields present higher similarity and can be more easily compared.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 6