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Text-mining as a methodology to assess eating disorder-relevant factors : comparing mentions of fitness tracking technology across online communities
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McCaig, Duncan, Bhatia, Sudeep, Elliott, Mark T., Walasek, Lukasz and Meyer, Caroline (2018) Text-mining as a methodology to assess eating disorder-relevant factors : comparing mentions of fitness tracking technology across online communities. International Journal of Eating Disorders, 51 (7). pp. 647-655. doi:10.1002/eat.22882
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WRAP-text-mining-methodology-assess-eating-disorder-relevant-factors-McCaig-2018.pdf - Accepted Version - Requires a PDF viewer. Download (1031Kb) | Preview |
Official URL: https://doi.org/10.1002/eat.22882
Abstract
Objective:
Text-mining offers a technique to identify and extract information from a large corpus of textual data. As an example, this study presents the application of text-mining to assess and compare interest in fitness tracking technology across eating disorder and health-related online communities.
Method:
A list of fitness tracking technology terms was developed, and communities (i.e., ‘subreddits’) on a large online discussion platform (Reddit) were compared regarding the frequency with which these terms occurred. The corpus used in this study comprised all comments posted between May 2015 and January 2018 (inclusive) on six subreddits – three eating disorder-related, and three relating to either fitness, weight-management or nutrition. All comments relating to the same ‘thread’ (i.e., conversation) were concatenated, and formed the cases used in this study (N=377,276).
Results:
Within the eating disorder-related subreddits, the findings indicated that a ‘pro-eating disorder’ subreddit, which is less recovery focused than the other eating disorder subreddits, had the highest frequency of fitness tracker terms. Across all subreddits, the weight-management subreddit had the highest frequency of the fitness tracker terms’ occurrence, and MyFitnessPal was the most frequently mentioned fitness tracker.
Discussion:
The technique exemplified here can potentially be used to assess group differences to identify at-risk populations, generate and explore clinically relevant research questions in populations who are difficult to recruit, and scope an area for which there is little extant literature. The technique also facilitates methodological triangulation of research findings obtained through more ‘traditional’ techniques, such as surveys or interviews.
| Item Type: | Journal Article | ||||||||
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| Subjects: | H Social Sciences > HM Sociology Q Science > QA Mathematics > QA76 Electronic computers. Computer science. Computer software R Medicine > RC Internal medicine |
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| Divisions: | Faculty of Medicine > Warwick Medical School Faculty of Science > WMG (Formerly the Warwick Manufacturing Group) |
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| Library of Congress Subject Headings (LCSH): | Data mining -- Health aspects, Text processing (Computer science), Eating disorders, Reddit (Firm), Physical fitness, Weight loss, Online social networks | ||||||||
| Journal or Publication Title: | International Journal of Eating Disorders | ||||||||
| Publisher: | John Wiley & Sons | ||||||||
| ISSN: | 1098-108X | ||||||||
| Official Date: | July 2018 | ||||||||
| Dates: |
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| Volume: | 51 | ||||||||
| Number: | 7 | ||||||||
| Page Range: | pp. 647-655 | ||||||||
| DOI: | 10.1002/eat.22882 | ||||||||
| Status: | Peer Reviewed | ||||||||
| Publication Status: | Published | ||||||||
| Access rights to Published version: | Restricted or Subscription Access | ||||||||
| RIOXX Funder/Project Grant: |
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