By Timon Oefelein Springer, Account Development Manager, North Western Europe Altmetrics for Librarians: a publisher dashboard, a university use case.

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Presentation transcript:

By Timon Oefelein Springer, Account Development Manager, North Western Europe Altmetrics for Librarians: a publisher dashboard, a university use case

1.Definition of key terms 2.Usage and citation metrics 3.Altmetrics = the missing puzzle piece 4.Dashboard for books and journals 5.A note on all the numbers 6.Important things to remember! 7.The rise of altmetric data 8.Correlation analysis 9.What‘s next? 10.2:AM Amsterdam 2015 Table of Contents

Usage or downloads (COUNTER stats) Scholarly citations (CrossRef, GoogleScholar, Scopus) Non-scholarly citations: Policy documents Blogs Wikipedia News Social media: Twitter, Weibo, Facebook, Google+, Pinterest, Reddit Reads on Online Reference Managers: Mendeley, CiteYouLike Other sources: YouTube, Reviews in F1000, PubPeer.. 1. Definition of key terms Altmetrics Articlel-mevel Metrics

Books Institutional Level Reports BR2 and BR3 Global Level Downloads per chapter and book title Journals Institutional Level Reports JR1, JR1a, JR2, JR5 Global Level 1. Downloads per journal 2. Journal Usage Factor 3. PubMed Link Out Stats 2. Usage metrics SpringerLink.comSpringer.com

2. Citation metrics SpringerLink.comSpringer.com Books Citations to all book chapters and title Journals Citations per article - Cites/article/web page - Citations per journal - Impact Factor - SNIP (normalized) - SJR (SCImago..) - Google’s H5 Index

3. Altmetrics = the missing piece of impact puzzle Usage and citations tell story about academic performance of article However, the metrics do not give insight into wider societal impact: Are policy makers citing and acting on the research? Is the media discussing the research? Is the public/academia discussing research on social media? And further, what is the size, speed, and demographic nature, of this societal response to research? The new altmetric data begins to answer these questions And therefore provides the „missing piece“ of the impact puzzle

4. New metrics dashboard for books! New metrics dashboard

4. The dashboard for books Data Sources

4. Click and the metrics take you here!

Whole Book Chapters

4. Example of mentions in social media

4. Example of Mendeley readers and demographics Click here to go to Mendeley for number of readers per chapter

Mainstream media Over 1000 outlets, see Altmetric.com for full list Blogs Manual list of over 8000 academic and non-academic blogs Policy documents Mainly English language but increasingly international Online Reference Managers Mendeley and Cite You Like Post Publication: PubPeer, Publons Social Media: Twitter, Facebook, Google+, Pinterest, Reddit, Sina-Weibo, Other Sources Wikipedia, Reviews in F1000, YouTube, etc. 4. Social media sources (tracked since 2011)

Mentions 4. SpringerLink – new altmetrics dashboard Citations

4. Special citations page on Springer.com

Social media authors or unique sources 4. Linkout is to article’s entry in Altmetric.com

SpringerLink shows the raw data or total number of mentions, 574 mentions Altmetric.com shows the total number of „unique sources“, 486 sources Altmetric.com shows weighted score, 379 (only for articles, not for chapters!) 5. A note on all the numbers

Using a scoreboard, each „mentioned by“ source is assigned points Blogs, Google+, Facebook sources: straightforward point conversion News and Twitter, Score modifiers: News: 1-10 points, depending one of four tiers Twitter: Re-tweets/re-posts = 0.85 points rather than 1 point Also, profile of tweeter is analyzed for reach, promiscuity, bias All points are added up for the final Altmetric Score Mendeley and CiteYouLike readers are excluded from the calculation 5. Altmetric scoreboard and modifiers 10

Each day, Altmetric tracks new mentions Each week, unique articles are shared So far, nearly 4 million articles and DOIs have been mentioned Mentions range in complexity, from quick shares to reviews 6. The rise of altmetric data

1.Altmetric data measures attention and not quality 2.Altmetric data measures public attention and not private attention 3.There are different types of data 4.Scores are not normalized and do not reflect norms within subject areas 5.Look beyond the numbers for a story of impact 6.Correlation studies: low correlation between altmetric attention & citations moderate correlation between altmetric attention & downloads 7. Things to remember!

8. Correlation analysis

9. What’s next! DOI Dataset ?

10. Want to learn more! October 2015 Keynote talk by Simon Singh Travel grants available, apply by 31 July Supported by:

This presentation is available for download:

Thank You! For Questions: Timon Oefelein: Account Development Manager, NW Europe Martijn Roelandse: Publishing Innovation Manager Altmetric.com: