Is there anybody out there ? Searching the social space for signs of intelligence

1. Is there anybody out there?Searching the social space for signs of intelligence Mike Taylor Research Specialist http://orcid.org/0000-0002-8534-5985 mi.taylor@elsevier.com

2. For much of the the last century, our only measurement of the impact of scholarly research has been through the counting and analysis of citation: one authoring researcher acknowledging the contribution of another authoring researcher. Significant, certainly, given these caveats, but in a wider social context citation analysis begins to look like an edge case. Can the measurement of sharing on social networks provide a wider view of how research is consumed in society, or is it all chatter and noise – and how do we detect the conversations of true significance?

3. The world according to citation • “I am writing an article and wish to cite another article”

4. The world according to alternative metrics • “I’m writing an article and might cite this” • “You should read this article if you’re interested in #thistopic” • “My PI wrote this paper” • “My daughter wrote this and I’m so proud” • “This article has a titivating title. Anyway, it made me laugh” • “These scientists are going to cure cancer”

5. The phenomenally rich world of alternative metrics • Social activity indicators: Twitter, Facebook, Delicious, Pintrest, Google+ • Scholarly activity indicators: Mendeley, Citeulike, Zotero • Scholarly articles: blogs, reviews • Mass media: news papers, TV • Re-usage indicators: data, code, graphics

6. An example from 2013 • Huge potential for social impact • Press campaign: front page storyon much of the UK press • Great publisher support fromNature • 1000s of tweets • But what’s missing?

7. The phenomenally poor world of alternative metrics Current alternative metrics don’t count or model: • Poorly referenced mass media • Stories about stories • The flow of the story • Social media about stories, replies, re-tweets • Influence on professional bodies • Representation to Government, Government policy

8. Not only are alternative metrics bigger than citations, they’re also different • Public vs private • Anonymous vs attributable • Persistent vs fleeting • Positive vs negative (counts and sentiment) • Real time vs slower • But article driven, formal links

9. The different characteristics of alternative metrics • Citation: one class of activity, with many sub-classes • Alternative metrics: several types of activity, with many classes and countless sub-classes (all vying with each other)

10. The power of intelligent conversation • Elevator pitch > monograph • A word in the ear of a Presidentversus • Engaging with millions • Patient-power • Lobbying interests

11. The chatter of (how shall we say this?) less than intelligent conversation • Not all communication is equal • Not all communication is between equals • Noise is not meritocratic • But is Twitter just meaningless noise?

12. The myth of social networks • Often assumed to be trivial, with a focus on titillating articles • An analysis of 13.5k papers revealed striking differences: • Top 0.5% of social activity – strong emphasis on policy, funding, areas where science and government overlap (stem cells, CERN, etc) • Top 0.5% of scholarly activity – primary research

13. The academic networks are building • Orcid / ODIN / THOR • Data DOIs • RDA data citation • Data metrics • Usage APIs / data • Open data, open articles

14. Mapping academic influence is becoming easier • Heading towards a paradigm shift in mapping academic influence • Academics probably won’t create negative links • This is a matter-of-fact network, flat, a statement of “what is” • Insufficient to understand social impact

15. Science in society • Open science, citizen science, open access, open data, cloud infrastructure, open source code, virtualization • Social networks, easy access to scholars • Too hard => too easy? • Explosion in communication and access

16. A partial view • Moving towards a more complete scholarly network • Data exists to get an idea of how research is being consumed in society • Too much missing to extrapolate • Almost entirely devoid of political context

17. Correlations • Not an even picture, there are threads of correlations – blogs – tweets – mass media • We can’t make simple conclusions • We don’t have enough data to make complex conclusions

18. Bigger data • Deeper: Talking about people, departments, companies, movements • More sensitive: Going from “being spoken about” to “what is being said” • Wider: “who is speaking”, “to whom are they speaking” • Further: “他們在中國說了什麼？”

19. The role of sociologists and economists • Social potential, professional and academic perspectives • Is $$$ a good reflection of impact? • People like to think of the “return on investment” model, but it’s not that easy, and the conclusions may be uncomfortable seen in isolation

20. Is a social impact index computable? • Social impact index = f(social capacity), f(social accessibility), f(social reach) • If has no capacity for effecting social change, if is incomprehensible, if no-one is aware of it… • We need the data and the maths to identify the intelligent versus the influential