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

被引:0
|
作者
Abdallah, Salam [1 ]
Khalil, Ashraf [2 ]
机构
[1] Abu Dhabi Univ, Coll Business, Abu Dhabi, U Arab Emirates
[2] Zayed Univ, Coll Technol Innovat, Abu Dhabi, U Arab Emirates
关键词
Text mining; Literature review; Big data analytics; Semantic analysis; Depression care; Major depressive disorder; MINING APPROACH; TEXT; DISORDER;
D O I
10.1108/IDD-03-2022-0020
中图分类号
G25 [图书馆学、图书馆事业]; G35 [情报学、情报工作];
学科分类号
1205 ; 120501 ;
摘要
PurposeThis 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/approachThis paper explores a hybrid methodology for literature review (HMLR), using text mining prior to systematic manual review.FindingsThe 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/valueThis 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.
引用
收藏
页码:305 / 323
页数:19
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