Tracking Behavioral Construct Use Through Citations: A Compositional Tree Kernel-Based Approach

Posted: 13 Jun 2015 Last revised: 6 Aug 2015

See all articles by Jingjing Li

Jingjing Li

University of Virginia - McIntire School of Commerce

Kai R. Larsen

Leeds School of Business; Information Systems Group; Gallup

Date Written: June 12, 2015

Abstract

The ever-increasing number of publications in the behavioral sciences has yielded a large set of behavioral theories, constructs and their relationships. In this study, we propose a novel method to discover this data set through construct-level citations. In behavioral science, the reuse, adaptation and modification of an existing behavioral construct often requires an explicit citation. However, finding the construct-level citations are not trivial, since citations are at the paper level of analysis. Based on state-of-the-art information extraction techniques, we propose an automatic construct-level citation extraction method, which consists of five steps: article crawling, article annotation, citation extraction, construct extraction and referring relation extraction. Serving as a proof-of-concept, our method is applied to a data set consisting of publication of two Information Systems journals, and is evaluated against human decisions. The initial results represent a promising opportunity of the application of our proposed method to a large set of behavioral publications.

Keywords: Information extraction, big data, constructs, citations, behavioral science

Suggested Citation

Li, Jingjing and Larsen, Kai R., Tracking Behavioral Construct Use Through Citations: A Compositional Tree Kernel-Based Approach (June 12, 2015). Available at SSRN: https://ssrn.com/abstract=2617913 or http://dx.doi.org/10.2139/ssrn.2617913

Jingjing Li (Contact Author)

University of Virginia - McIntire School of Commerce ( email )

P.O. Box 400173
Charlottesville, VA 22904-4173
United States

Kai R. Larsen

Leeds School of Business; Information Systems Group ( email )

995 Regent Dr.
Boulder, CO 80309-0419
United States

Gallup ( email )

901 F St NW
Washington, DC 20004
United States

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