Altmetrics: from hype to opportunitySeven use cases for altmetrics

Mike TaylorResearch Specialist

http://orcid.org/0000-0002-8534-5985mi.taylor@elsevier.com

• 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

• Some in or near production• Some need academic research• Some need business research• Some need environmental development

Seven reasons to use altmetrics

1…

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

Altmetric tools enable discovery of previously-hidden engagement and usage.

#1 Because They’re Interesting

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

Blogs, news items, reviews, social activity, scholarly activity

2…

Some articles have influence that is not revealed through citation.

Altmetrics provides alternative views of usage.

Status - Being used

#2 Discovering hidden impact

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

#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

3…

• 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

Data provided by Altmetric.com

4…

#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

• 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

5…

#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

• 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

6…

#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

• 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

7…

#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

• 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

• 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

• 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

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)