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Volumn 131, Issue 13, 2015, Pages e392-

Letter by Thoma et al regarding article, "A randomized trial of social media from Circulation"

Author keywords

[No Author keywords available]

Indexed keywords

CIRCULATION; EMERGENCY MEDICINE; HUMAN; INTERPERSONAL COMMUNICATION; KNOWLEDGE; LETTER; PRIORITY JOURNAL; PUBLICATION; RANDOMIZED CONTROLLED TRIAL (TOPIC); REPRODUCIBILITY; SOCIAL MEDIA; JOURNAL IMPACT FACTOR; TRENDS;

EID: 84929327855     PISSN: 00097322     EISSN: 15244539     Source Type: Journal    
DOI: 10.1161/CIRCULATIONAHA.114.014441     Document Type: Letter
Times cited : (4)

References (5)
  • 3
    • 84859897031 scopus 로고    scopus 로고
    • Can tweets predict citations? Metrics of social impact based on Twitter and correlation with traditional metrics of scientific impact
    • Eysenbach G. Can tweets predict citations? Metrics of social impact based on Twitter and correlation with traditional metrics of scientific impact. J Med Internet Res. 2011;13:e123. doi: 10.2196/jmir.2012.
    • (2011) J Med Internet Res , vol.13 , pp. e123
    • Eysenbach, G.1
  • 4
    • 84880445160 scopus 로고    scopus 로고
    • Social media release increases dissemination of original articles in the clinical pain sciences
    • Allen HG, Stanton TR, Di Pietro F, Moseley GL. Social media release increases dissemination of original articles in the clinical pain sciences. PLoS One. 2013;8:e68914. doi: 10.1371/journal.pone.0068914.
    • (2013) PLoS One , vol.8 , pp. e68914
    • Allen, H.G.1    Stanton, T.R.2    Di Pietro, F.3    Moseley, G.L.4
  • 5
    • 84929388492 scopus 로고    scopus 로고
    • Can social media increase medical journal article readership?
    • Accessed November 20, 2014
    • Aase L. Can social media increase medical journal article readership? Mayo Clinic Social Media Health Network. 2014. http://network.socialmedia.mayoclinic.org/discussion/can-social-media-increasemedical-journal-article-readership/. Accessed November 20, 2014.
    • (2014) Mayo Clinic Social Media Health Network
    • Aase, L.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.