Rodrigo Costas, Zohreh Zahedi & Paul Wouters
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Transcript of Rodrigo Costas, Zohreh Zahedi & Paul Wouters
Disentangling the meaning of ‘altmetrics’: content analysis of Web of Science scientific publications
Rodrigo Costas, Zohreh Zahedi & Paul WoutersCenter for Science and Technology Studies (CWTS-Leiden University)
23 June 2014
Introduction
• Altmetrics: new way of expanding the analysis of ‘impact’ of scientific products• Weak correlations with citations have been
observed (Haustein et al, 2014; Costas et al, 2014)• If they don’t capture the same concept of
impact as citations, then, • What kind of impact do altmetrics capture?• Content analysis of publications with altmetrics
(vs. publications with citation impact)
Research questions• Two main research questions:
• What disciplines have a higher density of altmetrics (vs. citations)?
• Which terms (topics) have a higher density of altmetrics (vs. citations)?
Methodology• Same WoS publications (matched by DOI with
Altmetric.com indicators) as in Costas et al (2014): half 2011, articles & reviews• 500,229 WoS publications, citations up to 2012
• Degree of ‘citedness’ or ‘altmetricness’ by• Disciplines (Subject Categories)• Topics (terms in the titles)
Main results – Subject categoriesTotal citation score (TCS)
Main results – Subject categoriesTotal altmetric score (TAS)
Main results – Term map
Main results – Term mapTCS
Main results – Term mapTAS
Conclusions & further research• Disciplinary analysis:
• Citations: stronger presence in fields like chemistry, physics or biomedical sciences• Altmetrics: stronger presence in the multidisciplinary journals, general medicine &
health and psychological and social sciences.
• Term map• Citations: stronger presence of terms related with natural sciences and more technical
topics• Altmetrics: stronger focus on social/laymen and medical-related terms, and less
frequent among chemical and physical terms.
• Citations: all topics, but also complex & technical ones. Altmetrics: not very technical/complex topics, more social & laymen ones.
• Further research• More elaborated linguistic analysis to further explore the hypothesis: are laymen terms
more prone to altmetrics?• Better categorization of terms (e.g. with MeSH) in order to delve into the
differences on the thematic orientation of citations and altmetrics.
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References
• Costas, R., Zahedi, Z., & Wouters, P. (2014). Do “altmetrics” correlate with citations? Extensive comparison of altmetric indicators with citations from a multidisciplinary perspective (p. 30). Leiden. Retrieved from http://www.cwts.nl/pdf/CWTS-WP-2014-001.pdf
• Haustein, S., Peters, I., Sugimoto, C. R., Thelwall, M., & Larivière, V. (2014). Tweeting Biomedicine : An Analysis of Tweets and Citations in the Biomedical Literature. Journal of the Association for Information Sciences and Technology, 65(4), 656–669. doi:10.1002/asi
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