Top Articles (Article-Level Metrics)

 
 
Rank Article Tweets Tweets per MonthA
Tweets Influence FactorB
Twimpact Factor (tw7)C Twindex7D
 
41
Use of Twitter Among Local Health Departments: An Analysis of Information Sharing, Engagement, and Action
Brad L Neiger, Rosemary Thackeray, Scott H Burton, Callie R Thackeray, Jennifer H Reese
J Med Internet Res 2013;15(8):e177
(Aug 19, 2013)
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1 0.17 0.00 40 95
 
 
42
A Study of Innovative Features in Scholarly Open Access Journals
Bo-Christer Björk
J Med Internet Res 2011;13(4):e115
(Dec 16, 2011)
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9 1.50 0.00 39 95
 
 
43
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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46 18.28 0.00 38 95
 
 
44
Collaborative Biomedicine in the Age of Big Data: The Case of Cancer
Abdul R Shaikh, Atul J Butte, Sheri D Schully, William S Dalton, Muin J Khoury, Bradford W Hesse
J Med Internet Res 2014;16(4):e101
(Apr 7, 2014)
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43 7.49 0.00 38 95
 
 
45
A Lot of Action, But Not in the Right Direction: Systematic Review and Content Analysis of Smartphone Applications for the Prevention, Detection, and Management of Cancer
Jacqueline Lorene Bender, Rossini Ying Kwan Yue, Matthew Jason To, Laetitia Deacken, Alejandro R Jadad
J Med Internet Res 2013;15(12):e287
(Dec 23, 2013)
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9 1.50 0.00 38 100
 
 
46
Disordered Eating in a Digital Age: Eating Behaviors, Health, and Quality of Life in Users of Websites With Pro-Eating Disorder Content
Rebecka Peebles, Jenny L Wilson, Iris F Litt, Kristina K Hardy, James D Lock, Julia R Mann, Dina LG Borzekowski
J Med Internet Res 2012;14(5):e148
(Oct 25, 2012)
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7 1.17 0.00 38 90
 
 
47
Transparency of Health-Apps for Trust and Decision Making
Urs-Vito Albrecht
J Med Internet Res 2013;15(12):e277
(Dec 30, 2013)
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4 0.67 0.00 38 95
 
 
48
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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48 11.63 0.00 36 100
 
 
49
The Behavioral Intervention Technology Model: An Integrated Conceptual and Technological Framework for eHealth and mHealth Interventions
David C Mohr, Stephen M Schueller, Enid Montague, Michelle Nicole Burns, Parisa Rashidi
J Med Internet Res 2014;16(6):e146
(Jun 5, 2014)
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46 11.98 0.00 35 95
 
 
50
Misleading Health-Related Information Promoted Through Video-Based Social Media: Anorexia on YouTube
Shabbir Syed-Abdul, Luis Fernandez-Luque, Wen-Shan Jian, Yu-Chuan Li, Steven Crain, Min-Huei Hsu, Yao-Chin Wang, Dorjsuren Khandregzen, Enkhzaya Chuluunbaatar, Phung Anh Nguyen, Der-Ming Liou
J Med Internet Res 2013;15(2):e30
(Feb 13, 2013)
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2 0.33 0.00 35 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.