Cristin-resultat-ID: 941373
Sist endret: 10. januar 2013 19:17
NVI-rapporteringsår: 2012
Resultat
Vitenskapelig artikkel
2012

HealthTrust: A Social Network Approach for Retrieving Online Health Videos

Bidragsytere:
  • Luis Fernandez-Luque
  • Randi Karlsen og
  • Genevieve B Melton

Tidsskrift

Journal of Medical Internet Research
ISSN 1438-8871
e-ISSN 1438-8871
NVI-nivå 2

Om resultatet

Vitenskapelig artikkel
Publiseringsår: 2012
Volum: 14
Hefte: 1
Sider: e22
Open Access

Importkilder

Scopus-ID: 2-s2.0-84860547693
Isi-ID: 000301925700030

Beskrivelse Beskrivelse

Tittel

HealthTrust: A Social Network Approach for Retrieving Online Health Videos

Sammendrag

Background: Social media are becoming mainstream in the health domain. Despite the large volume of accurate and trustworthy health information available on social media platforms, finding good-quality health information can be difficult. Misleading health information can often be popular (eg, antivaccination videos) and therefore highly rated by general search engines. We believe that community wisdom about the quality of health information can be harnessed to help create tools for retrieving good-quality social media content. Objectives: To explore approaches for extracting metrics about authoritativeness in online health communities and how these metrics positively correlate with the quality of the content. Methods: We designed a metric, called HealthTrust, that estimates the trustworthiness of social media content (eg, blog posts or videos) in a health community. The HealthTrust metric calculates reputation in an online health community based on link analysis. We used the metric to retrieve YouTube videos and channels about diabetes. In two different experiments, health consumers provided 427 ratings of 17 videos and professionals gave 162 ratings of 23 videos. In addition, two professionals reviewed 30 diabetes channels. Results: HealthTrust may be used for retrieving online videos on diabetes, since it performed better than YouTube Search in most cases. Overall, of 20 potential channels, HealthTrust’s filtering allowed only 3 bad channels (15%) versus 8 (40%) on the YouTube list. Misleading and graphic videos (eg, featuring amputations) were more commonly found by YouTube Search than by searches based on HealthTrust. However, some videos from trusted sources had low HealthTrust scores, mostly from general health content providers, and therefore not highly connected in the diabetes community. When comparing video ratings from our reviewers, we found that HealthTrust achieved a positive and statistically significant correlation with professionals (Pearson r10 = .65, P = .02) and a trend toward significance with health consumers (r7 = .65, P = .06) with videos on hemoglobinA1c, but it did not perform as well with diabetic foot videos. Conclusions: The trust-based metric HealthTrust showed promising results when used to retrieve diabetes content from YouTube. Our research indicates that social network analysis may be used to identify trustworthy social media in health communities.

Bidragsytere

Luis Fernández Luque

Bidragsyterens navn vises på dette resultatet som Luis Fernandez-Luque
  • Tilknyttet:
    Forfatter
    ved Institutt for informatikk ved UiT Norges arktiske universitet
  • Tilknyttet:
    Forfatter
    ved NORCE Teknologi ved NORCE Norwegian Research Centre AS

Randi Karlsen

  • Tilknyttet:
    Forfatter
    ved Institutt for informatikk ved UiT Norges arktiske universitet
  • Tilknyttet:
    Forfatter
    ved NORCE Teknologi ved NORCE Norwegian Research Centre AS

Genevieve B Melton

  • Tilknyttet:
    Forfatter
    ved Saint Mary's University of Minnesota
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