A systematic method for search term selection in systematic reviews

The wide variety of readily available electronic media grants anyone the freedom to retrieve published references from almost any area of research around the world. Despite this privilege, keeping up with primary research evidence is almost impossible because of the increase in professional publishi...

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Bibliographic Details
Published in:Research synthesis methods Vol. 5; no. 2; pp. 87 - 97
Main Authors: Thompson, Jenna, Davis, Jacqueline, Mazerolle, Lorraine
Format: Journal Article
Language:English
Published: England 01.06.2014
Subjects:
Data Mining - methods
Machine Learning
Natural Language Processing
Pattern Recognition, Automated
Periodicals as Topic
Research Design
Review Literature as Topic
Search Engine - methods
Semantics
Software
Vocabulary, Controlled
systematic search
term
semantics
systematic review
ISSN:1759-2887
Online Access:Get more information
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Summary:The wide variety of readily available electronic media grants anyone the freedom to retrieve published references from almost any area of research around the world. Despite this privilege, keeping up with primary research evidence is almost impossible because of the increase in professional publishing across disciplines. Systematic reviews are a solution to this problem as they aim to synthesize all current information on a particular topic and present a balanced and unbiased summary of the findings. They are fast becoming an important method of research across a number of fields, yet only a small number of guidelines exist on how to define and select terms for a systematic search. This article presents a replicable method for selecting terms in a systematic search using the semantic concept recognition software called leximancer (Leximancer, University of Queensland, Brisbane, Australia). We use this software to construct a set of terms from a corpus of literature pertaining to transborder interventions for drug control and discuss the applicability of this method to systematic reviews in general. This method aims to contribute a more 'systematic' approach for selecting terms in a manner that is entirely replicable for any user.
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ISSN:1759-2887
DOI:10.1002/jrsm.1096