Top Articles (Article-Level Metrics)

 
 
Rank Article Tweets Tweets per MonthA
Tweets Influence FactorB
Twimpact Factor (tw7)C Twindex7D
 
41
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 4.00 0.00 4 25
 
 
42
Experiential Virtual Scenarios With Real-Time Monitoring (Interreality) for the Management of Psychological Stress: A Block Randomized Controlled Trial
Andrea Gaggioli, Federica Pallavicini, Luca Morganti, Silvia Serino, Chiara Scaratti, Marilena Briguglio, Giulia Crifaci, Noemi Vetrano, Annunziata Giulintano, Giuseppe Bernava, Gennaro Tartarisco, Giovanni Pioggia, Simona Raspelli, Pietro Cipresso, Cinzia Vigna, Alessandra Grassi, Margherita Baruffi, Brenda Wiederhold, Giuseppe Riva
J Med Internet Res 2014;16(7):e167
(Jul 8, 2014)
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4 4.00 0.00 12 80
 
 
43
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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4 4.00 0.00 529 100
 
 
44
How an Online Intervention to Prevent Excessive Gestational Weight Gain Is Used and by Whom: A Randomized Controlled Process Evaluation
Margaret Mochon Demment, Meredith Leigh Graham, Christine Marie Olson
J Med Internet Res 2014;16(8):e194
(Aug 20, 2014)
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4 0.00 0.00 4 65
 
 
45
Characterizing the Followers and Tweets of a Marijuana-Focused Twitter Handle
Patricia Cavazos-Rehg, Melissa Krauss, Richard Grucza, Laura Bierut
J Med Internet Res 2014;16(6):e157
(Jun 27, 2014)
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3 3.00 0.00 28 100
 
 
46
Detecting Disease Outbreaks in Mass Gatherings Using Internet Data
Elad Yom-Tov, Diana Borsa, Ingemar J Cox, Rachel A McKendry
J Med Internet Res 2014;16(6):e154
(Jun 18, 2014)
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3 3.00 0.00 15 90
 
 
47
Designing Messaging to Engage Patients in an Online Suicide Prevention Intervention: Survey Results From Patients With Current Suicidal Ideation
Ursula Whiteside, Anita Lungu, Julie Richards, Gregory E Simon, Sarah Clingan, Jaeden Siler, Lorilei Snyder, Evette Ludman
J Med Internet Res 2014;16(2):e42
(Feb 7, 2014)
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2 2.00 0.00 4 45
 
 
48
Exploring the Value of Technology to Stimulate Interprofessional Discussion and Education: A Needs Assessment of Emergency Medicine Professionals
Jennifer Riley, Melissa McGowan, Linda Rozmovits
J Med Internet Res 2014;16(6):e162
(Jun 30, 2014)
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2 2.00 0.00 5 55
 
 
49
Physician Response Time When Communicating With Patients Over the Internet
Per Egil Kummervold, Jan-Are K Johnsen
J Med Internet Res 2011;13(4):e79
(Nov 1, 2011)
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2 2.00 0.00 27 90
 
 
50
Quantifying Short-Term Dynamics of Parkinson’s Disease Using Self-Reported Symptom Data From an Internet Social Network
Max Little, Paul Wicks, Timothy Vaughan, Alex Pentland
J Med Internet Res 2013;15(1):e20
(Jan 24, 2013)
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2 2.00 0.00 29 100
 
 
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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.