SIG Meta - Meta Research in Information Systems

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Paper Type

Complete

Paper Number

1702

Description

IS research has linked collaborators from diverse domains. IS research requires selecting and addressing an appropriate intradisciplinary or interdisciplinary scope. Identifying gaps in the current literature and deciding when and how collaborations among different disciplines may be fruitful poses challenges. We propose a process to analyze a corpus of documents from any topic, to identify potential collaboration areas. A text analytics process is used to find areas of commonality and exclusivity among questions addressed in existing IS work by analyzing abstracts in papers from multiple disciplines studying 'software piracy.' We use term-term co-occurrence to find all the terms used in close proximity to the topic. We identify which terms are most prominent in each discipline, show quantitatively how these usages coincide or diverge across disciplines, measure the overlap between pairs of disciplines, and identify clusters of terms shared among disciplines. Specific findings from this case of software piracy are presented.

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Aug 10th, 12:00 AM

The Use of Text Analytics to Investigate Concepts in Intra- and Inter-disciplinary Software Piracy Research

IS research has linked collaborators from diverse domains. IS research requires selecting and addressing an appropriate intradisciplinary or interdisciplinary scope. Identifying gaps in the current literature and deciding when and how collaborations among different disciplines may be fruitful poses challenges. We propose a process to analyze a corpus of documents from any topic, to identify potential collaboration areas. A text analytics process is used to find areas of commonality and exclusivity among questions addressed in existing IS work by analyzing abstracts in papers from multiple disciplines studying 'software piracy.' We use term-term co-occurrence to find all the terms used in close proximity to the topic. We identify which terms are most prominent in each discipline, show quantitatively how these usages coincide or diverge across disciplines, measure the overlap between pairs of disciplines, and identify clusters of terms shared among disciplines. Specific findings from this case of software piracy are presented.

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