Top Articles (Article-Level Metrics)

 
 
Rank Article Tweets Tweets per MonthA
Tweets Influence FactorB
Twimpact Factor (tw7)C Twindex7D
 
31
Can Tweets Predict Citations? Metrics of Social Impact Based on Twitter and Correlation with Traditional Metrics of Scientific Impact
Gunther Eysenbach
J Med Internet Res 2011;13(4):e123
(Dec 16, 2011)
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5 5.00 0.00 529 100
 
 
32
Motives for Participating in a Web-Based Nutrition Cohort According to Sociodemographic, Lifestyle, and Health Characteristics: The NutriNet-Santé Cohort Study
Caroline Méjean, Fabien Szabo de Edelenyi, Mathilde Touvier, Emmanuelle Kesse-Guyot, Chantal Julia, Valentina A Andreeva, Serge Hercberg
J Med Internet Res 2014;16(8):e189
(Aug 7, 2014)
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4 4.77 0.00 4 55
 
 
33
Mind the Gap: Social Media Engagement by Public Health Researchers
Brett Keller, Alain Labrique, Kriti M Jain, Andrew Pekosz, Orin Levine
J Med Internet Res 2014;16(1):e8
(Jan 14, 2014)
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4 4.00 0.00 84 100
 
 
34
Wikis and Collaborative Writing Applications in Health Care: A Scoping Review
Patrick M Archambault, Tom H van de Belt, Francisco J Grajales III, Marjan J Faber, Craig E Kuziemsky, Susie Gagnon, Andrea Bilodeau, Simon Rioux, Willianne LDM Nelen, Marie-Pierre Gagnon, Alexis F Turgeon, Karine Aubin, Irving Gold, Julien Poitras, Gunther Eysenbach, Jan AM Kremer, France Légaré
J Med Internet Res 2013;15(10):e210
(Oct 8, 2013)
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4 4.00 0.00 75 100
 
 
35
Virtual Communities of Practice: Overcoming Barriers of Time and Technology
Kieran Walsh, Stephen Barnett
J Med Internet Res 2014;16(7):e185
(Jul 29, 2014)
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4 4.00 0.00 8 65
 
 
36
Caught in the Web: A Review of Web-Based Suicide Prevention
Mee Huong Lai, Thambu Maniam, Lai Fong Chan, Arun V Ravindran
J Med Internet Res 2014;16(1):e30
(Jan 28, 2014)
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4 4.00 0.00 4 25
 
 
37
Mobile Health Applications for the Most Prevalent Conditions by the World Health Organization: Review and Analysis
Borja Martínez-Pérez, Isabel de la Torre-Díez, Miguel López-Coronado
J Med Internet Res 2013;15(6):e120
(Jun 14, 2013)
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4 4.00 0.00 106 100
 
 
38
Understanding the Factors That Influence the Adoption and Meaningful Use of Social Media by Physicians to Share Medical Information
Brian S McGowan, Molly Wasko, Bryan Steven Vartabedian, Robert S Miller, Desirae D Freiherr, Maziar Abdolrasulnia
J Med Internet Res 2012;14(5):e117
(Sep 24, 2012)
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4 4.00 0.00 142 100
 
 
39
Predictors of eHealth Usage: Insights on The Digital Divide From the Health Information National Trends Survey 2012
Emily Kontos, Kelly D Blake, Wen-Ying Sylvia Chou, Abby Prestin
J Med Internet Res 2014;16(7):e172
(Jul 16, 2014)
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3 3.00 0.00 38 95
 
 
40
Is Biblioleaks Inevitable?
Adam G Dunn, Enrico Coiera, Kenneth D Mandl
J Med Internet Res 2014;16(4):e112
(Apr 22, 2014)
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3 3.00 0.00 91 100
 
 
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Total Tweets
 
Tweets per Month
 
Tweets Influence Factor
 
Twimpact Factor (TWIF) tw7
 
Twindex7

A Tweets per month statistic may be artifically inflated for newly published articles

B Tweets Influence Factor (TIF): number of tweets x avg. influence of tweeters (influence is determined by how often all tweets of that person are retweeted by others)

C Twimpact Factor (TWIF) tw7: Number of mentionings in tweets (tweetations) within first 7 days after article publication (Eysenbach 2011)

D Twindex7 (Eysenbach 2011): Rank percentile of this article when its twimpact factor (tw7) is compared to 19 previously published articles. Range 0-100, with higher scores reflecting higher impact on Twitter. Articles with a Twindex greater than 75 have a 75% chance of being highly cited (top quartile by citation), articles with a Twindex less than 75 have a 7% chance to be highly cited.