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Analysis of user activities on popular medical forums

Journal of physics. Conference series, 2017-10, Vol.913 (1), p.12007 [Peer Reviewed Journal]

Published under licence by IOP Publishing Ltd ;2017. This work is published under http://creativecommons.org/licenses/by/3.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;ISSN: 1742-6588 ;EISSN: 1742-6596 ;DOI: 10.1088/1742-6596/913/1/012007

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  • Title:
    Analysis of user activities on popular medical forums
  • Author: Kamalov, M V ; Dobrynin, V Y ; Balykina, Y E ; Martynov, R S
  • Subjects: Internet resources ; Machine learning ; Natural language processing
  • Is Part Of: Journal of physics. Conference series, 2017-10, Vol.913 (1), p.12007
  • Description: The paper is devoted to detailed investigation of users' behavior and level of expertise on online medical forums. Two popular forums were analyzed in terms of presence of experts who answer health related questions and participate in discussions. This study provides insight into the quality of medical information that one can get from the web resources, and also illustrates relationship between approved medical experts and popular authors of the considered forums. During experiments several machine learning and natural language processing methods were evaluated against to available web content to get further understanding of structure and distribution of information about medicine available online nowadays. As a result of this study the hypothesis of existing correlation between approved medical experts and popular authors has been rejected.
  • Publisher: Bristol: IOP Publishing
  • Language: English
  • Identifier: ISSN: 1742-6588
    EISSN: 1742-6596
    DOI: 10.1088/1742-6596/913/1/012007
  • Source: Geneva Foundation Free Medical Journals at publisher websites
    AUTh Library subscriptions: ProQuest Central
    IOPscience (Open Access)
    Institute of Physics Open Access Journal Titles
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