Top Articles (Article-Level Metrics)

 
 
Rank Article Tweets Tweets per MonthA
Tweets
Influence
Factor
B
Twimpact Factor (tw7)C Twindex7D
 
171
Searching for Cancer Information on the Internet: Analyzing Natural Language Search Queries
Judith L Bader, Mary Frances Theofanos
J Med Internet Res 2003;5(4):e31
(Dec 11, 2003)
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4 0.67 0.00 3 100
 
 
172
Sources of Information and Behavioral Patterns in Online Health Forums: Observational Study
Fabian Sudau, Tim Friede, Jens Grabowski, Janka Koschack, Philip Makedonski, Wolfgang Himmel
J Med Internet Res 2014;16(1):e10
(Jan 14, 2014)
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4 0.67 0.00 10 80
 
 
173
Cancer Survivorship in the Age of YouTube and Social Media: A Narrative Analysis
Wen-Ying Sylvia Chou, Yvonne Hunt, Anna Folkers, Erik Augustson
J Med Internet Res 2011;13(1):e7
(Jan 17, 2011)
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4 0.67 0.00 30 100
 
 
174
Patients’ Engagement With “Sweet Talk” – A Text Messaging Support System for Young People With Diabetes
Victoria Franklin, Alexandra Greene, Annalu Waller, Stephen Greene, Claudia Pagliari
J Med Internet Res 2008;10(2):e20
(Jun 30, 2008)
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4 0.67 0.00 1 95
 
 
175
Animated Randomness, Avatars, Movement, and Personalization in Risk Graphics
Holly O Witteman, Andrea Fuhrel-Forbis, Harindra C Wijeysundera, Nicole Exe, Mark Dickson, Lisa Holtzman, Valerie C Kahn, Brian J Zikmund-Fisher
J Med Internet Res 2014;16(3):e80
(Mar 18, 2014)
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4 0.93 0.00 4 50
 
 
176
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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4 123.84 0.00 4 50
 
 
177
Adolescents Just Do Not Know What They Want: A Qualitative Study to Describe Obese Adolescents’ Experiences of Text Messaging to Support Behavior Change Maintenance Post Intervention
Kyla L Smith, Deborah A Kerr, Ashley A Fenner, Leon M Straker
J Med Internet Res 2014;16(4):e103
(Apr 8, 2014)
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4 1.10 0.00 4 45
 
 
178
Open Source, Open Standards, and Health Care Information Systems
Carl J Reynolds, Jeremy C Wyatt
J Med Internet Res 2011;13(1):e24
(Feb 17, 2011)
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4 0.67 0.00 8 30
 
 
179
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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4 0.67 0.00 40 95
 
 
180
Young Men, Mental Health, and Technology: Implications for Service Design and Delivery in the Digital Age
Louise A Ellis, Philippa Collin, Tracey A Davenport, Patrick J Hurley, Jane M Burns, Ian B Hickie
J Med Internet Res 2012;14(6):e160
(Nov 22, 2012)
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4 0.67 0.00 52 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.