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

1. Exploring disciplinary differences
in the use of social media
in scholarly communication
Stefanie Haustein

2. 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**

3. 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**

4. 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).

5. 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).