Top Articles (Article-Level Metrics)

 
 
Rank Article Tweets Tweets per MonthA
Tweets Influence FactorB
Twimpact Factor (tw7)C Twindex7D
 
181
Validation and Reliability of a Smartphone Application for the International Prostate Symptom Score Questionnaire: A Randomized Repeated Measures Crossover Study
Jae Heon Kim, Soon-Sun Kwon, Sung Ryul Shim, Hwa Yeon Sun, Young Myoung Ko, Dong-Il Chun, Won Jae Yang, Yun Seob Song
J Med Internet Res 2014;16(2):e38
(Feb 10, 2014)
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4 0.76 0.00 4 45
 
 
182
Investigating the Congruence of Crowdsourced Information With Official Government Data: The Case of Pediatric Clinics
Minki Kim, Yuchul Jung, Dain Jung, Cinyoung Hur
J Med Internet Res 2014;16(2):e29
(Feb 3, 2014)
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4 0.73 0.00 4 40
 
 
183
Caught in the Web: A Review of Web-Based Suicide Prevention
Mee Huong Lai, Thambu Maniam, Lai Fong Chan, Arun V Ravindran
J Med Internet Res 2014;16(1):e30
(Jan 28, 2014)
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4 0.70 0.00 4 25
 
 
184
Broad Reach and Targeted Recruitment Using Facebook for an Online Survey of Young Adult Substance Use
Danielle E. Ramo, Judith J. Prochaska
J Med Internet Res 2012;14(1):e28
(Feb 23, 2012)
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4 0.67 0.00 10 35
 
 
185
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
 
 
186
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
 
 
187
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
 
 
188
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
 
 
189
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
 
 
190
Online Access to Doctors' Notes: Patient Concerns About Privacy
Elisabeth Vodicka, Roanne Mejilla, Suzanne G Leveille, James D Ralston, Jonathan D Darer, Tom Delbanco, Jan Walker, Joann G Elmore
J Med Internet Res 2013;15(9):e208
(Sep 26, 2013)
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4 0.67 0.00 32 100
 
 
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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.