HealthTrust: trust-based retrieval of you tube's diabetes channels

  • Authors:

  • Luis Fernandez-Luque;Randi Karlsen;Genevieve B. Melton

  • Affiliations:

  • Computer Science Department, University of Tromso, Tromso, Norway;Northern Research Institute, Tromso, Norway;University of Minnesota, Minneapolis, MN, USA

  • Venue:
  • Proceedings of the 20th ACM international conference on Information and knowledge management
  • Year:
  • 2011

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Abstract

The Internet has become one of the main sources of consumer health information. Health consumers have access to ever-growing health information resources, especially since the rise of the Social Media. For example, over 20.000 videos have been uploaded by American hospitals on to YouTube. To find health videos is challenging because of factors like tags spamming and misleading information. Previous studies have found difficulties when searching for good health videos in YouTube, including false information (e.g., herbal cures for diabetes or cancer). Our objective was to extract information about the trustworthiness of the diabetes YouTube's channels using link analysis of the diabetes online community by developing an algorithm, called HealthTrust, based on Hyperlink-Induced Topic Search (HITS) for ranking the most authoritative diabetes channels. The ranked list of channels from HealthTrust was compared with the list of the most relevant diabetes channels from YouTube. Two healthcare professionals made a blinded classification of channels based on whether they would recommend the channel to a patient. HealthTrust performed better for retrieving channels recommended by the professional reviewers. HealthTrust performed several times better than YouTube for filtering out the worst channels (i.e., those not recommended by any expert reviewer).