Top Articles (Article-Level Metrics)

 
 
Rank Article Tweets Tweets per MonthA
Tweets Influence FactorB
Twimpact Factor (tw7)C Twindex7D
 
1
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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142 23.67 0.00 529 100
 
 
2
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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112 22.69 0.00 91 100
 
 
3
A Spanish Pillbox App for Elderly Patients Taking Multiple Medications: Randomized Controlled Trial
José Joaquín Mira, Isabel Navarro, Federico Botella, Fernando Borrás, Roberto Nuño-Solinís, Domingo Orozco, Fuencisla Iglesias-Alonso, Pastora Pérez-Pérez, Susana Lorenzo, Nuria Toro
J Med Internet Res 2014;16(4):e99
(Apr 4, 2014)
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92 16.68 0.00 51 100
 
 
4
Massive Open Online Courses on Health and Medicine: Review
Tharindu Rekha Liyanagunawardena, Shirley Ann Williams
J Med Internet Res 2014;16(8):e191
(Aug 14, 2014)
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72 57.23 0.00 58 100
 
 
5
Representation of Health Conditions on Facebook: Content Analysis and Evaluation of User Engagement
Timothy M Hale, Akhilesh S Pathipati, Shiyi Zan, Kamal Jethwani
J Med Internet Res 2014;16(8):e182
(Aug 4, 2014)
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70 44.29 0.00 29 95
 
 
6
Social Network Sites as a Mode to Collect Health Data: A Systematic Review
Fahdah Alshaikh, Farzan Ramzan, Salman Rawaf, Azeem Majeed
J Med Internet Res 2014;16(7):e171
(Jul 14, 2014)
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65 28.79 0.00 53 100
 
 
7
Mapping Physician Twitter Networks: Describing How They Work as a First Step in Understanding Connectivity, Information Flow, and Message Diffusion
Ranit Mishori, Lisa Oberoi Singh, Brendan Levy, Calvin Newport
J Med Internet Res 2014;16(4):e107
(Apr 14, 2014)
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63 12.13 0.00 41 95
 
 
8
mHealth and Mobile Medical Apps: A Framework to Assess Risk and Promote Safer Use
Thomas Lorchan Lewis, Jeremy C Wyatt
J Med Internet Res 2014;16(9):e210
(Sep 15, 2014)
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59 261.29 0.00 59 100
 
 
9
Numeracy and Literacy Independently Predict Patients’ Ability to Identify Out-of-Range Test Results
Brian J Zikmund-Fisher, Nicole L Exe, Holly O Witteman
J Med Internet Res 2014;16(8):e187
(Aug 8, 2014)
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56 38.58 0.00 25 95
 
 
10
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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47 7.83 0.00 75 100
 
 
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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.