eprintid: 1562394 rev_number: 31 eprint_status: archive userid: 608 dir: disk0/01/56/23/94 datestamp: 2017-07-09 01:33:04 lastmod: 2021-10-06 22:54:20 status_changed: 2017-07-17 12:18:35 type: article metadata_visibility: show creators_name: Stansfield, C creators_name: O'Mara-Eves, A creators_name: Thomas, J title: Text mining for search term development in systematic reviewing: A discussion of some methods and challenges ispublished: pub divisions: UCL divisions: B16 divisions: B14 divisions: J81 keywords: Clustering, information retrieval, systematic search, text mining note: Copyright © 2017 John Wiley & Sons, Ltd. This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions. abstract: Using text mining to aid the development of database search strings for topics described by diverse terminology has potential benefits for systematic reviews; however, methods and tools for accomplishing this are poorly covered in the research methods literature. We briefly review the literature on applications of text mining for search term development for systematic reviewing. We found that the tools can be used in 5 overarching ways: improving the precision of searches; identifying search terms to improve search sensitivity; aiding the translation of search strategies across databases; searching and screening within an integrated system; and developing objectively derived search strategies. Using a case study and selected examples, we then reflect on the utility of certain technologies (term frequency-inverse document frequency and Termine, term frequency, and clustering) in improving the precision and sensitivity of searches. Challenges in using these tools are discussed. The utility of these tools is influenced by the different capabilities of the tools, the way the tools are used, and the text that is analysed. Increased awareness of how the tools perform facilitates the further development of methods for their use in systematic reviews. date: 2017-09 date_type: published official_url: http://doi.org/10.1002/jrsm.1250 oa_status: green full_text_type: other language: eng primo: open primo_central: open_green article_type_text: Journal Article verified: verified_manual elements_id: 1300709 doi: 10.1002/jrsm.1250 lyricists_name: O'Mara-Eves, Alison lyricists_name: Stansfield, Claire lyricists_name: Thomas, James lyricists_id: AJOMA15 lyricists_id: CMSTA07 lyricists_id: JTHOA32 actors_name: Stansfield, Claire actors_name: Laslett, David actors_id: CMSTA07 actors_id: DLASL34 actors_role: owner actors_role: impersonator full_text_status: public publication: Reseach Synthesis Methods volume: 8 number: 3 pagerange: 355-365 event_location: England issn: 1759-2887 citation: Stansfield, C; O'Mara-Eves, A; Thomas, J; (2017) Text mining for search term development in systematic reviewing: A discussion of some methods and challenges. Reseach Synthesis Methods , 8 (3) pp. 355-365. 10.1002/jrsm.1250 <https://doi.org/10.1002/jrsm.1250>. Green open access document_url: https://discovery.ucl.ac.uk/id/eprint/1562394/1/Stansfield%20et%20al.%202017_Pre-Print_Text%20mining%20for%20search%20term%20development.pdf