A Semi-Auto Text Mining Approach for Literature Review

Abstract

The emergence of powerful information technologies (IT) has changed innovation and entrepreneurship in significant ways. Research in IT for entrepreneurship is relatively new and there is a growing interest from academics for further studies on investigating this area of research. This study reviews research carried out in the domain of IT for entrepreneurship. A total of 1005 papers, published between 1980 and 2021 were used to uncover the latent topics addressed in this domain. A topic modeling (LDA) algorithm was used to automate the process of extracting the initial research topics from the data. The results show that IT for entrepreneurship studies are classified into six aspects of research: entrepreneurship initiative and innovation, strategy, business process management and operation management, entrepreneurship education, industry analysis, and business model. The results raise awareness of IT-associated entrepreneurship areas of research, provide useful insights for future research, and informs practice in this domain of study.

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No public copy is stored for this record, so only the metadata is cited.

Stored only when both papers are in the corpus — 3 citations exist upstream.

Papers that cite the same references — the relational fallback while embeddings are still backfilling.