Top Articles (Article-Level Metrics)

 
 
Rank Article Tweets Tweets per MonthA
Tweets
Influence
Factor
B
Twimpact Factor (tw7)C Twindex7D
 
21
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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6 6.00 0.00 529 100
 
 
22
Changes Over Time in the Utilization of Disease-Related Internet Information in Newly Diagnosed Breast Cancer Patients 2007 to 2013
Christoph Kowalski, Eva Kahana, Kathrin Kuhr, Lena Ansmann, Holger Pfaff
J Med Internet Res 2014;16(8):e195
(Aug 26, 2014)
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6 6.00 0.00 14 80
 
 
23
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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6 6.00 0.00 25 95
 
 
24
Patient Experiences With Full Electronic Access to Health Records and Clinical Notes Through the My HealtheVet Personal Health Record Pilot: Qualitative Study
Susan S Woods, Erin Schwartz, Anais Tuepker, Nancy A Press, Kim M Nazi, Carolyn L Turvey, W. Paul Nichol
J Med Internet Res 2013;15(3):e65
(Mar 27, 2013)
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6 6.00 0.00 70 100
 
 
25
Internet Search and Krokodil in the Russian Federation: An Infoveillance Study
Andrey Zheluk, Casey Quinn, Peter Meylakhs
J Med Internet Res 2014;16(9):e212
(Sep 18, 2014)
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6 15.50 0.00 5 45
 
 
26
Opportunities and Challenges for Smartphone Applications in Supporting Health Behavior Change: Qualitative Study
Laura Dennison, Leanne Morrison, Gemma Conway, Lucy Yardley
J Med Internet Res 2013;15(4):e86
(Apr 18, 2013)
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5 5.00 0.00 97 95
 
 
27
Communicating the Experience of Chronic Pain and Illness Through Blogging
Pamela Katz Ressler, Ylisabyth S. Bradshaw, Lisa Gualtieri, Kenneth Kwan Ho Chui
J Med Internet Res 2012;14(5):e143
(Oct 23, 2012)
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5 5.00 0.00 57 95
 
 
28
An Internet-Based Epidemiological Investigation of the Outbreak of H7N9 Avian Influenza A in China Since Early 2013
Chen Mao, Xin-Yin Wu, Xiao-Hong Fu, Meng-Yang Di, Yuan-Yuan Yu, Jin-Qiu Yuan, Zu-Yao Yang, Jin-Ling Tang
J Med Internet Res 2014;16(9):e221
(Sep 25, 2014)
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5 31.00 0.00 5 65
 
 
29
The Management of Acute Adverse Effects of Breast Cancer Treatment in General Practice: A Video-Vignette Study
Moyez Jiwa, Anne Long, Tim Shaw, Georgina Pagey, Georgia Halkett, Vinita Pillai, Xingqiong Meng
J Med Internet Res 2014;16(9):e204
(Sep 3, 2014)
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4 4.59 0.00 4 55
 
 
30
Effects of a Guided Web-Based Smoking Cessation Program With Telephone Counseling: A Cluster Randomized Controlled Trial
Michael Mehring, Max Haag, Klaus Linde, Stefan Wagenpfeil, Antonius Schneider
J Med Internet Res 2014;16(9):e218
(Sep 24, 2014)
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4 20.67 0.00 4 55
 
 
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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.