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Identifying Interdisciplinary Intersections Through Analytics: Software Piracy Case
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AI
DOI：10.1080/08874417.2023.2300651.png)
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Abstract
En 中文
IS researchers’ interest in interdisciplinary research is strong, given the widespread use of IT across disciplines. IS researchers have challenges identifying topics in the IS literature that offer interdisciplinary collaboration opportunities. While team collaboration research suggests that knowledge of shared concepts helps ensure team success, scant guidelines for achieving this goal exist. To address this gap, we demonstrate a text analytics tool focusing on “software piracy” as a case study. The tool analyzes abstracts, employing term-term co-occurrence to identify commonalities and exclusivity for a topic across disciplines. By assessing term prominence, intersection degrees, and shared clusters, the tool helps pinpoint potential interdisciplinary research foci. This approach identifies intersecting terminologies in software piracy and can be applied to other interdisciplinary phenomena in IS or other disciplines. Finally, the approach can be deployed to build multiple sets of relevant topic terms for a domain in different clusters for various collaborative communities.
Keywords:
Text analytics
interdisciplinary
knowledge contribution
software piracy
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