SIG Meta - Meta Research in Information Systems
Event Title
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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.
Recommended Citation
Hughes, Jerald; Chavarria, Juan A.; and Andoh-Baidoo, Francis Kofi, "The Use of Text Analytics to Investigate Concepts in Intra- and Inter-disciplinary Software Piracy Research" (2022). AMCIS 2022 Proceedings. 2.
https://aisel.aisnet.org/amcis2022/sig_meta/sig_meta/2
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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