Top Articles (Article-Level Metrics)

 
 
Rank Article Tweets Tweets per MonthA
Tweets Influence FactorB
Twimpact Factor (tw7)C Twindex7D
 
41
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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38 3.17 54.00 103 100
 
 
42
Do Cancer Patients Tweet? Examining the Twitter Use of Cancer Patients in Japan
Atsushi Tsuya, Yuya Sugawara, Atsushi Tanaka, Hiroto Narimatsu
J Med Internet Res 2014;16(5):e137
(May 27, 2014)
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37 20.12 0.00 36 100
 
 
43
Mobile Applications for Diabetics: A Systematic Review and Expert-Based Usability Evaluation Considering the Special Requirements of Diabetes Patients Age 50 Years or Older
Madlen Arnhold, Mandy Quade, Wilhelm Kirch
J Med Internet Res 2014;16(4):e104
(Apr 9, 2014)
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37 10.92 0.00 22 90
 
 
44
Patient and Public Views on Electronic Health Records and Their Uses in the United Kingdom: Cross-Sectional Survey
Serena A Luchenski, Julie E Reed, Cicely Marston, Chrysanthi Papoutsi, Azeem Majeed, Derek Bell
J Med Internet Res 2013;15(8):e160
(Aug 23, 2013)
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37 3.43 43.00 28 85
 
 
45
Assessing the Applicability of E-Therapies for Depression, Anxiety, and Other Mood Disorders Among Lesbians and Gay Men: Analysis of 24 Web- and Mobile Phone-Based Self-Help Interventions
Tomas Rozbroj, Anthony Lyons, Marian Pitts, Anne Mitchell, Helen Christensen
J Med Internet Res 2014;16(7):e166
(Jul 3, 2014)
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36 55.80 0.00 18 95
 
 
46
Did You Hear the One About the Doctor? An Examination of Doctor Jokes Posted on Facebook
Matthew A Davis, Carol Sue Haney, William B Weeks, Brenda E Sirovich, Denise L Anthony
J Med Internet Res 2014;16(2):e41
(Feb 13, 2014)
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36 6.97 0.00 13 75
 
 
47
The Use and Significance of a Research Networking System
Maninder Kahlon, Leslie Yuan, John Daigre, Eric Meeks, Katie Nelson, Cynthia Piontkowski, Katja Reuter, Rachael Sak, Brian Turner, Griffin M Weber, Anirvan Chatterjee
J Med Internet Res 2014;16(2):e46
(Feb 7, 2014)
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36 6.72 0.00 30 95
 
 
48
Collection and Visualization of Dietary Behavior and Reasons for Eating Using Twitter
Melanie Hingle, Donella Yoon, Joseph Fowler, Stephen Kobourov, Michael Lee Schneider, Daniel Falk, Randy Burd
J Med Internet Res 2013;15(6):e125
(Jun 24, 2013)
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36 3.00 42.00 14 75
 
 
49
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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35 155.00 0.00 35 95
 
 
50
Guess Who’s Not Coming to Dinner? Evaluating Online Restaurant Reservations for Disease Surveillance
Elaine O Nsoesie, David L Buckeridge, John S Brownstein
J Med Internet Res 2014;16(1):e22
(Jan 22, 2014)
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35 5.96 0.00 32 95
 
 
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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.