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Finding Reasons for Vaccination Hesitancy: Evaluating Semi-Automatic Coding of Internet Discussion Forums
Linnaeus University, Faculty of Technology, Department of computer science and media technology (CM). (ISOVIS)ORCID iD: 0000-0001-6164-7762
Linnaeus University, Faculty of Technology, Department of computer science and media technology (CM). (ISOVIS)ORCID iD: 0000-0002-0519-2537
Potsdam University, Germany.
2019 (English)In: MEDINFO 2019: Health and Wellbeing e-Networks for All: Proceedings of the 17th World Congress on Medical and Health Informatics / [ed] Lucila Ohno-Machado and Brigitte Séroussi, IOS Press, 2019, p. 348-352Conference paper, Published paper (Refereed)
Abstract [en]

Computer-assisted text coding can facilitate the analysis of large text collections. To evaluate the functionality of providing an analyst with a ranked list of suggestions for suitable text codes, we used a data set of discussion posts, which had been manually coded for reasons given for taking a stance on the topic of vaccination. We trained a logistic regression classifier to rank these reasons according to the probability that they would be present in the post. The approach was evaluated for its ability to include the expected reasons among the n top-ranked reasons, using an n between 1 and 6. The logistic regression-based ranking was more effective than the baseline, which ranked reasons according to their frequency in the training data. To provide such a list of possible codes, ranked by logistic regression, could therefore be a useful feature in a tool for text coding.

Place, publisher, year, edition, pages
IOS Press, 2019. p. 348-352
Series
Studies in Health Technology and Informatics, ISSN 0926-9630, E-ISSN 1879-8365 ; 264
Keywords [en]
Vaccination Refusal, Text Mining, Supervised Machine Learning
National Category
Language Technology (Computational Linguistics)
Research subject
Computer Science, Information and software visualization
Identifiers
URN: urn:nbn:se:lnu:diva-82449DOI: 10.3233/SHTI190241ISBN: 978-1-64368-003-3 (electronic)ISBN: 978-1-64368-002-6 (print)OAI: oai:DiVA.org:lnu-82449DiVA, id: diva2:1313824
Conference
17th World Congress on Medical and Health Informatics (MEDINFO '19), 25-30 August, 2019, Lyon, France.
Projects
Navigating in streams of opinions: Extracting and visualising arguments in opinionated texts
Funder
Swedish Research Council, 2016-06681Available from: 2019-05-06 Created: 2019-05-06 Last updated: 2019-08-28

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Skeppstedt, MariaKerren, Andreas

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CiteExportLink to record
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Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
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More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
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  • Other locale
More languages
Output format
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  • asciidoc
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