1. Altmetrics and the publisher
I’m Mike Taylor, I’m a research
specialist and I work for Elsevier Labs
http://labs.elsevier.com

2. What is Altmetrics?
• Article-level metrics
• It is the collection, the counting and
interpretation of non-formal citation of
scholarly documents
• And what does non-formal citation mean?
• It’s when you save a work in Mendeley or
Zotero or Figshare or you bookmark it in
Del.icio.us or share it in Facebook or Twitter
• Not “talking about work” but “referencing it”
Next up – obligatory slide about Elsevier

3. Obligatory slide about what Elsevier is
doing
• Quite a lot!
• Altmetric.com tool has been on Scopus as a
mandatory tool for nearly a year
• Lots of articles are appearing on Elsevier
websites (www.elsevierconnect.com,
www.researchtrends.com)
• The publishing units have plans and projects
• And there’s my work
Next up – what altmetrics says about altmetrics

4. What do people say about Altmetrics?
• “The speed of altmetrics presents the
opportunity to create real-time
recommendation and collaborative filtering
systems”
• “they’re great for measuring impact in [the]
diverse scholarly ecosystem”
• “Altmetrics expand our view of what impact
looks like”
• All from altmetrics.org/manifesto
Next up – what curmudgeonly professors say about altmetrics

5. What do people say about Altmetrics?
• Professor David Calquhoun of UCL: “Altmetrics
are cheap gimmickry that encourage gaming
the system, ie dishonesty. I do wish that kids
with computers would get off the backs of real
scientists.”
Next up – Altmetric.com

6. What does altmetric.com look like?
• Examples of ImpactStory and Altmetric.com
Next up – Impact Story

7. What does ImpactStory.org look like?
• Examples of Im
• Also Plum Analytics and various other tools
• http://altmetrics.org/tools/
Next up – why you don’t have to do anything!

8. What you have to do!
• Great news!
• You don’t have to do anything!
• Other people will do it for you, whether you
like it or not!
• But getting altmetric.com or ImpactStory on
your website is easy, so technical integration is
a doddle
Next up – how ANYONE can view altmetrics!

9. American Journal of Hypertension
• 10.1093/ajh/hps090
• 10.1093/ajh/hps088
Journal of the American Society of
• 10.1093/ajh/hps097 Hypertension
• 10.1093/ajh/hps089
• 10.1093/ajh/hpt008
• 10.1093/ajh/hps100 10.1016/S1933-1711(13)00022-3
• 10.1093/ajh/hpt010 10.1016/j.jash.2013.01.004
• 10.1093/ajh/hpt028 10.1016/j.jash.2013.01.003
• 10.1093/ajh/hpt041
• 10.1093/ajh/hpt042 10.1016/j.jash.2013.01.006, 10.1038/495425a
• 10.1093/ajh/hps098 10.1016/j.jash.2013.01.001
•
•
10.1093/ajh/hps065
10.1093/ajh/hps119
10.1016/j.jash.2012.12.008 10.1038/495426a
10.1016/j.jash.2012.12.006
•
•
10.1093/ajh/hpt009
10.1093/ajh/hps072 10.1016/j.jash.2012.12.003
10.1038/495430a
• 10.1093/ajh/hps092
• 10.1093/ajh/hps099 10.1016/j.jash.2013.01.002 10.1038/495433a
• 10.1093/ajh/hps095 10.1016/j.jash.2012.12.007
• 10.1093/ajh/hps096 10.1016/S1933-1711(13)00023-5
10.1016/j.jash.2013.01.007 Next up – why does this matter?

10. Why you should do more
• What difference will Open Access use to your
non-specialist usage?
• Will funders require more social impact
statements?
• Is Open Access more than just “sticking a PDF
up on a website”?
Next up – the anatomy of a story

11. The anatomy of a story
• “The £5 spit test for cancer”
• Front page news
• Wide-spread coverage
• Nature moved mountains to
make it accessible
• Massive social impact potential
• A really big deal

12. Altmetric.com

13. ImpactStory
http://www.impactstory.org/collection/dnwpb3

14. Disappointment? The power of PR?
900
800
700
600
500
400
300
200
100
Saved (eg, Mendeley, Citeulike, Delicious)
0
Discussed (ie, Twitter via Topsy Twitter API)

15. Seeing (or not) the bigger picture
• 300+ comments on
The Guardian
• Dozens of news stories
• 100 comments on the
Daily Mail
• Social Media buzz
Next up – “Once upon a time…”

16. Current state of altmetrics is v0.1
• Link-based
• Counting
• Limited interpretation, because numbers
aren’t much
• Founded in 2010
• Didn’t make much impact until 2012
Next up – kicking up a gear

17. V0.2, 0.5 are much more interesting
• Crawling
• Similiarity-based
• Temporal analysis
• Semantic analysis
Next up - Complex stuff with known solutions

18. And this is an easy thing to do
• Finding ‘similar stories’ with a ‘similar
fingerprint’ in a ‘similar timescale’ is a known
problem
• Dozens of start-ups do this
• Links are easy and cheap, and are a great
place to start
Next up – but these are just meaningless numbers… right?

19. But even so… it’s just a bag of numbers
• How do different professions behave?
• What’s the fingerprint of non-scholarly
behaviour?
• How is it changing over time?
• When will the numbers make real-time
recommendations a possibility?
• Is it easier to game than JIF?

20. What work needs to be done?
• Semantics
• Temporal analysis
• Surveys of real-life behaviour
Next up – the end

21. The end: a history and future of
scholarly impact
• Is only the beginning
• After citation 
• After downloads and page views 
• After scholarly interest 
• After mass media 
• After non-scholarly interest 
• Tracking linguistic terms, semantic
linking, memes analysis: semantometrics