Stefanie Haustein Lightning talk at NISO Altmetrics Initiative meeting
 

Stefanie Haustein Lightning talk at NISO Altmetrics Initiative meeting

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Stefanie Haustein – "Exploring disciplinary differences in the use of social media in scholarly communication" Lightning talk at NISO Altmetrics Initiative meeting in San Francisco, CA October 9, ...

Stefanie Haustein – "Exploring disciplinary differences in the use of social media in scholarly communication" Lightning talk at NISO Altmetrics Initiative meeting in San Francisco, CA October 9, 2013

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    Stefanie Haustein Lightning talk at NISO Altmetrics Initiative meeting Stefanie Haustein Lightning talk at NISO Altmetrics Initiative meeting Presentation Transcript

    • Exploring disciplinary differences in the use of social media in scholarly communication Stefanie Haustein
    • Mendeley coverage and correlation with citations of PubMed/WoS Based on 1.4 million PubMed papers published between 2010 and 2012 and covered by WoS. Mendeley readers were collected via the API. Mendeley coverage is based on all papers, correlations are calculated for papers published in 2011, which were at least read once, to reduce biases. Specialties (NSF classification) are shown, when they contained at least 100 papers in the PubMed/WoS set and at least 30 papers from 2011 on Mendeley. Bubble size represents average number of readers per document on Mendeley. • coverage: 66.2% • documents with ≥1 Mendeley reader: 951,421 • mean number of readers per document with ≥1 Mendeley reader: 9.7 • correlation with citations of P(2011)read: ρ = 0.456**
    • Twitter Twitter coverage and correlation with citations of PubMed/WoS Based on 1.4 million PubMed papers published between 2010 and 2012 and covered by WoS. Tweets were collected from Altmetric.com. Twitter coverage is based on all papers, correlations are calculated for papers published in 2011, which were at least tweeted once, to reduce biases. Specialties (NSF classification) are shown, when they contained at least 100 papers in the PubMed/WoS set and at least 30 tweeted papers in 2011. Bubble size represents average number of tweets per tweeted document. • coverage: 9.4% • documents with ≥1 tweets: 134.924 • mean number of tweets per tweeted document: 2.5 • correlation with citations of P(2011)read: ρ = 0.157**
    • Mendeley coverage and correlation with citations of PubMed/WoS Based on 1.4 million PubMed papers published between 2010 and 2012 and covered by WoS. Mendeley readers were collected via the API. Mendeley coverage is based on all papers, correlations are calculated for papers published in 2011, which were at least read once, to reduce biases. Specialties (NSF classification) are shown, when they contained at least 100 papers in the PubMed/WoS set and at least 30 papers from 2011 on Mendeley. Bubble size represents average number of readers per document on Mendeley. Correlations are significant at the 0.01 (**) or 0.05 (*) level (two-tailed).
    • Twitter coverage and correlation with citations of PubMed/WoS Based on 1.4 million PubMed papers published between 2010 and 2012 and covered by WoS. Tweets were collected from Altmetric.com. Twitter coverage is based on all papers, correlations are calculated for papers published in 2011, which were at least tweeted once, to reduce biases. Specialties (NSF classification) are shown, when they contained at least 100 papers in the PubMed/WoS set and at least 30 tweeted papers in 2011. Bubble size represents average number of tweets per tweeted document. Correlations are significant at the 0.01 (**) or 0.05 (*) level (two-tailed).