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Using a hybrid methodology for literature review: a case study in depression research

Salam Abdallah (College of Business, Abu Dhabi University, Abu Dhabi, United Arab Emirates)
Ashraf Khalil (College of Technological Innovation, Zayed University, Abu Dhabi, United Arab Emirates)

Information Discovery and Delivery

ISSN: 2398-6247

Article publication date: 3 November 2023

Issue publication date: 2 July 2024

232

Abstract

Purpose

This study aims to understand and a lay a foundation of how analytics has been used in depression management, this study conducts a systematic literature review using two techniques – text mining and manual review. The proposed methodology would aid researchers in identifying key concepts and research gaps, which in turn, will help them to establish the theoretical background supporting their empirical research objective.

Design/methodology/approach

This paper explores a hybrid methodology for literature review (HMLR), using text mining prior to systematic manual review.

Findings

The proposed rapid methodology is an effective tool to automate and speed up the process required to identify key and emerging concepts and research gaps in any specific research domain while conducting a systematic literature review. It assists in populating a research knowledge graph that does not reach all semantic depths of the examined domain yet provides some science-specific structure.

Originality/value

This study presents a new methodology for conducting a literature review for empirical research articles. This study has explored an “HMLR” that combines text mining and manual systematic literature review. Depending on the purpose of the research, these two techniques can be used in tandem to undertake a comprehensive literature review, by combining pieces of complex textual data together and revealing areas where research might be lacking.

Keywords

Citation

Abdallah, S. and Khalil, A. (2024), "Using a hybrid methodology for literature review: a case study in depression research", Information Discovery and Delivery, Vol. 52 No. 3, pp. 305-323. https://doi.org/10.1108/IDD-03-2022-0020

Publisher

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Emerald Publishing Limited

Copyright © 2023, Emerald Publishing Limited

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