Altmetrics : from hype to opportunity Seven use cases for altmetrics
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Transcript of Altmetrics : from hype to opportunity Seven use cases for altmetrics
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Altmetrics: from hype to opportunitySeven use cases for altmetrics
Mike TaylorResearch Specialist
http://orcid.org/[email protected]
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• Elsevier Labs is a Research and Development group in Elsevier IT
• Part of Enterprise Architecture• Linked / semantic data, tech / acquisition
evaluations, ORCID, cloud – from Labs to business
• Text mining, natural language processing, profiling, altmetrics – in various stages of transition
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• Some in or near production• Some need academic research• Some need business research• Some need environmental development
Seven reasons to use altmetrics
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Researchers – like other human beings – are social, engaged and interested.
Enabling discovery of networks and networks is interesting.
Status - Live
#1 Because They’re Interesting
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Altmetric tools enable discovery of previously-hidden engagement and usage.
#1 Because They’re Interesting
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健康医療分野における三つの都市伝説:ほうれん草には鉄が多い・電磁波は体に悪い・ワクチンで自閉症になる 根拠の無さを説明した後にどう考えが変わったかのアンケート結果と考察も(英文記事)
Tweet about an article I wrote
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Blogs, news items, reviews, social activity, scholarly activity
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Some articles have influence that is not revealed through citation.
Altmetrics provides alternative views of usage.
Status - Being used
#2 Discovering hidden impact
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Substantial evidence that scholars have a high degree of engagement in science / social issues:• Funding• Policy• Gender• Open access• Cross-over interest revealed in social activity,
scholarly activity in top 0.5% articles, even in the absence of “mass media” interest
• Data provided by Altmetric.com
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#3 Predicting citationBeing able to predict highly cited papers is of great use to scholars, publishers, institutions.
Altmetric data can play a role in prediction.
Status – academic research
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• There is evidence that some highly cited papers can be predicted using a mix of data
• Twitter is not a good source of this data• Mendeley / Citeulike are likely good sources• Identifying influential papers makes them
influential• Can this work for non-English language papers?• Can this work for non-DOI, non-IF articles and
papers?• => Sigint – signal intelligence might open up
developing world research to wider attention
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Data provided by Altmetric.com
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#4 Real-time informationKnowing what other people are reading and discussing reduces the amount of time needed to search the literature.
Altmetrics enables this discovery
Status – business research
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• An obvious use-case – to effectively crowd-source literature searches
• But a very small % of papers receives a very % of attention
• Altmetric data needs to be associated other data, eg, network analysis and similarity
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#5 Re-useThere is increasing effort into re-use of data sets (and other research outputs, eg, code)
As well as representing usage, altmetrics data can include re-usage data
Status – requires investigation and environmental change
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• Data from data repositories – Data Dryad, and others
• Code from github• Graphics (and data, etc) on Figshare• Downside: data repository is fragmented,
600+ repositories registered at databib.org• Upside: Datacite, ODIN, ORCID, DOI,
Draft Declaration of Data Citation Principles
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#6 Performance comparisonPublishers, institutions and platforms differ in their abilities to promote use, re-use and sharing.
Altmetric data can allow (cautious) comparative, like-for-like, benchmarking
Status – community investigation
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• If altmetrics measures something that predicts citation, social reach, re-usage, etc, then the promotion of efficient strategies that enable optimum activity is of interest to all of us
• Private data reveals one UK university doubling its data within a year by one hire
• Start-ups: minimanuscript.com, www.growkudos.com
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#7 Social reachThe importance understanding social impact of research is increasing.
Altmetric data might offer us the ability to compute the social reach of research, a component of social impact.
Status - uncertain
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• Encouraging researchers to use, re-use material is one issue
• Encouraging the lay community to access, consume, is another
• Detecting usage amongst the legislative, regulatory communities is another
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• Detecting usage in the scholarly community is one issue
• Detecting usage in the lay community is another
• Detecting usage amongst the legislative, regulatory communities is very difficult
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• Social impact can be very visible, but it’s usually very stealthy.
• Serious papers can (and do) get 1000s of tweets
• The headline papers – the top 1%, 2% - are misleading
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Conclusion• We serve communities of humans: we
shouldn’t rule out human interest as trivial.• As data, investment and analysis grows,
altmetrics will become a vital source of data (and will probably not be known as altmetrics)