Citation theoriesand their application to altmetrics

Rodrigo CostasCentre for Science and Technology Studies (CWTS-Leiden University), the Netherlands

Stefanie HausteinUniversité de Montréal, Canada

@RodrigoCostas1

@stefhaustein

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Types of altmetrics• Research impact on (mostly) social media• Heterogeneity• Reference management: reader counts • Recommending: recommendations • Blogging: blog mentions • Microblogging: microposts• others Need to differentiate!

Lack of meaning and theoretical foundations

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Altmetrics in the light of citation theory• Normative theory (Kaplan, 1965; Merton, 1973) ‘Ethos of science’ (Merton, 1973)• Communism• Universalism

• Social constructivist theoryDeviation from normative behavior• Persuasion• Matthew effect

• Concept symbols (Small, 1978)symbolic act: association of document with concept

• Disinterestedness• Organized skepticism

• Perfunctory citations• Negative citations, etc.

Research Evaluation

Content Analysis & Science Mapping

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Altmetrics in the light of citation theory• Normative theory (Kaplan, 1965; Merton, 1973) ‘Ethos of science’ (Merton, 1973)• Communism• Universalism

• Social constructivist theoryDeviation from normative behavior• Persuasion• Matthew effect

• Concept symbols (Small, 1978)symbolic act: association of document with concept

• Disinterestedness• Organized skepticism

• Perfunctory citations• Negative citations, etc.

How do these theoriesapply to altmetrics?• Saved in Mendeley• Mentioned in a tweet• Reviewed on F1000• Cited in a blog post

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Normative theory• F1000– Faculty members are “world's leading scientists”– Reviewers “must sign a statement to indicate that

the article has been selected […] entirely on its scientific merit and […] not been influenced”

• Mendeley– Pre-citation context– Anonymous nature of saving process– Not all papers are read

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Normative theory• Blogs

– similar to citations– “The post author should have read and

understood the entire work cited [and] report accurately and thoughtfully on the research.” (ResearchBlogging)

– open uncontrolled nature of blogs• Twitter

– brevity– humor and entertainment aspect– diffusion channel– diverse user groups and user motivations

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Social constructivist theory• Twitter– Matthew effect (internally):

reinforced by Twitter affordancesextremely skewed distributions

– Matthew effect (externally): popularity of high-impact journals

• Blogs– Persuasion: driving force in blogging– Matthew effect: focus on high-impact journals

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Social constructivist theory• Mendeley– Matthew effect: popularity of high-impact journals– Anonymous nature of saving to Mendeley

• F1000– Matthew effect (externally): focus on high-impact

journals– Subjectivity of reviewers– Recommendations are linked to reviewers

Concept symbols• Blogs– Authors associated cited documents with concept

• Twitter, F1000, Mendeley– Concepts condensed in tags

#altmetrics

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Conclusions• Normative approach• High applicability for F1000• Moderate for Mendeley• Low applicability for Twitter or blogs

• Social constructivist approach• High applicability for Twitter and blogs• Moderate for F1000

• Concept symbols• High applicability for Twitter, F1000, Mendeley

and blogsTheory highlights heterogeneity of acts

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Conclusions and outlook• Research evaluation

• Higher applicability for Mendeley and F1000• No applicability for Twitter

• Content analysis and mapping• High applicability for F1000, Mendeley, Twitter and blogs

but as exploration and description of ‘perception of science’

Theoretical discussions help to:• uncover acts behind metrics• interprete meaning of metrics

Need for other theories and frameworks

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Questions?

http://arxiv.org/abs/1502.05701