An Investigation of Applying Centrality Measures as Indicators of Citation-Based Relation in Relational Information Retrieval: A Pilot Study

Abbaspour, Javad; Naghshineh, Nader; Fadaie, Gholamreza; Osareh, Farideh

An Investigation of Applying Centrality Measures as Indicators of Citation-Based Relation in Relational Information Retrieval: A Pilot Study

Volume 19, Issue 1
Spring 2013

Pages 149-161

Research on Information Science and Public Libraries

Document Type : Original Article

Authors

Javad Abbaspour ¹

Nader Naghshineh ²

Gholamreza Fadaie ³

Farideh Osareh ⁴

¹ PhD student in Information Science and Knowledge, University of Tehran, Shiraz University Scholarship

² Assistant Professor, Department of Information Science and Knowledge, University of Tehran

³ Professor, Department of Information Science and Epistemology, University of Tehran

⁴ Professor, Department of Information Science and Knowledge, Shahid Chamran University of Ahvaz

Abstract

Purpose: this is a pilot study tends to investigate correlation between centrality measures with bibliographic coupling as a well-known citation-based document similarity measure.
Methodology: using citation analysis method, 40 research articles belonging to four engineering/pure disciplines (Physics, Chemistry, Biology, and computer) and four Humanities and Social disciplines (Economics, Education, Psychology, and Sociology) published in 2011 and indexed in Web of Knowledge Database besides their citation links with 4000 other article(100 citation per article) were randomly selected as research population. Data were extracted and analyzed using UCINet and Bibexcel programs.
Findings: findings demonstrated that there are high significant correlation (α=0/01) between centrality measures and bibliographic coupling; and so, centrality measures have potential features for further analysis in order to apply them as new citation- based similarity measures.
Originality/Value: this research suggested new citation-based similarity measures which can be applied in databases and search engines algorithms to measure similarity of documents more accurately.

Keywords

Centrality Measures

Bibliographic Coupling

Similarity Measures

Relational Information Retrieval

Citation-based Retrieval