Altmetrics: from hype to opportunity Seven use cases for altmetrics Mike Taylor Research Specialist

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 citation Being 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 information Knowing 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-use There 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 PrinciplesDraft Declaration of Data Citation Principles 6…

#6 Performance comparison Publishers, 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, 7…

#7 Social reach The 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)