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Metrics: The New Black?
Metrics: The New Black?
Metrics: The New Black?
Metrics: The New Black?
Metrics: The New Black?
Metrics: The New Black?
Metrics: The New Black?
Metrics: The New Black?
Metrics: The New Black?
Metrics: The New Black?
Metrics: The New Black?
Metrics: The New Black?
Metrics: The New Black?
Metrics: The New Black?
Metrics: The New Black?
Metrics: The New Black?
Metrics: The New Black?
Metrics: The New Black?
Metrics: The New Black?
Metrics: The New Black?
Metrics: The New Black?
Metrics: The New Black?
Metrics: The New Black?
Metrics: The New Black?
Metrics: The New Black?
Metrics: The New Black?
Metrics: The New Black?
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Metrics: The New Black?

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How will the proliferation of altmetrics (ALMs) change our understanding of user behavior in scholarly publishing?

How will the proliferation of altmetrics (ALMs) change our understanding of user behavior in scholarly publishing?

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  • 1. Metrics:The New Black? Kristen Fisher Ratan NFAIS 2012
  • 2. The web is getting personal
  • 3. Can Web Metrics Indicate Research Impact?
  • 4. Metrics:The New Black? Kristen Fisher Ratan NFAIS 2012
  • 5. Research Dissemination IS Research Impact
  • 6. Dissemination creates indicatorsof impact Publication DisseminationArticle Level • Citations • Web usageMetrics (ALMs) • Star Ratings • Social bookmarking • Community rating • Media/blog coverage • Commenting activity • and more…
  • 7. ALMs: Two Traditional Use Cases Author Researcher/Writer/Journalist Self-Metrics Research & Discovery Measure the impact and reach of Gauge value of any article with their work post-publication peer review Benchmark article performance Conduct custom searches that against others account for research impact Collect relevant articles and Evaluate publication decisions to organize based upon array of maximize the impact of their work criteria Gain insight into article’s impact Understand readership within context of related research Communicate impact of research to Analyze trends/behaviors across a employers, funders, potential database of academic literature collaborators The Third? Meta-analysis using large datasets of ALMs
  • 8. Beyond the Article
  • 9. Usage isn’t always indicative 1595 Tweets
  • 10. Inside the Article
  • 11. Powerpoint download feature inadvertently tracked sub-article usage
  • 12. New feature may be able to track cut/paste activities
  • 13. 90%
  • 14. To Measure is to Know
  • 15. Let’s get tracking• Cut/paste• Figures opened, downloaded• Links clicked• Time spent on article page• Supplemental info viewed• Authors’ info viewed• Pathways that info travels• ALMs viewed and used To understand true use of context
  • 16. What Might Data Drive?• Tenure and promotion• Grants• Reputation• Discovery• Prioritization $ Attention: the new currency
  • 17. Caveats and concerns• Missed citation data• Data sources aren’t reliable• Digital addresses change• Usage doesn’t mean useful• Deliberate gaming• Context
  • 18. Next: Context-Mining
  • 19. Thank You!Kristen Fisher Ratan kratan@plos.org

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