University Rankings,the Triple Helix Modeland Webometrics:Opening Pandora’s Box

1. University Rankings,
the Triple Helix Model
and Webometrics:
Opening Pandora’s Box
Prof. Han Woo Park
Dept of Media & Communication, Yeungnam Univ
Pieter Stek
Doctoral Student, Delft University of Technology

2. Disclaimer
The views expressed in this presentation
reflect personal opinions which may or may
not coincide with the views of the
organization with which the authors are
affiliated.

4. https://www.triplehelixassociation.org/webinar-series/university-rankings

5. Aims
• Understanding the methodologies and
impact of existing university rankings
• Discussing how advances in Webometrics
may lead to new university rankings
• Opening Pandora’s box: towards a Triple
Helix Ranking of Universities

6. Agenda
• Introducing university rankings
• Webometrics of academia
• A Triple Helix Ranking concept
– Debating the pros and cons

7. University rankings

8. Which is your favorite?

9. Rankings compared
Criterion QS THE Shanghai Leiden
Academic
publications, Nobel,
Fields
20% 36% 90% 100%
Reputation survey 50% 33%
Faculty/student ratio 20% 4.5%
International 10% 7.5%
Other 8.25% (doctor-bachelor
ratio)
2.5% (industry income)
8.25% (income)
10% (per
capita
performan
ce)

10. Some national rankings
• Joongang Ilbo (Korea)
Faculty research (33%), education and financial (30%),
reputation and alumni (20%), internationalization (17%)
• U.S. News and World Report (USA)
Reputation (22.5%), selectivity (12.5%), faculty resources
(20%), graduation/retention rates (30%), financial (15%)
• Zeit CHE Ranking (Germany)
At course level, course features + student and faculty
opinion survey
• Research Assessment Framework (UK)
At department level, focusing on ‘originality, significance
and rigor’, thus including research impact
• Etc.

11. Alternative: Trojan Condom Ranking

12. PartySchoolRanking

13. Rankings summary & claims
• Matter to students, parents, employers and
governments
• So they matter to universities
• Propositions:
– Rankings are changing universities
– Rankings are a policy tool
– Rankings reflect consumer power

14. Webometrics of academia

15. Internet presence
• Essential questions:
– Who is mentioned? (content analysis)
– By whom? (citation network analysis)
on the internet
– What does this say about the underlying academic
system?
• We present some findings published in
Scientometrics:
– Barnett et al. (2013) – [B]
– Lee & Park (2012) – [L]
– Chung & Park (2012) – [C]

16. Universities
• [B] Universities network centrality on the academic
internet (e.g. harvard.edu, tudelft.nl, yu.ac.kr) has a
statistically significant correlation with:
– University size
– Number of Nobel Prizes
– Rankings (U.S. News)
– Doctoral degrees yes/no
– English-speaking yes/no
– Bandwidth capacity
– Physical distance is irrelevant
• And at the national level:
– Citations, co-authorship, student exchange, total number of
weblinks

17. Webometrics rankings?
• They exist: webometrics.info, which is
based on an inbound link measure
• [B] Academic web network centrality is
predictive of rankings (U.S. News)
• [L] Web visibility is also highly predictive of
rankings (Shanghai)
• There is an ‘English speaking’ bias/benefit

18. Scholars
• [C] Online visibility of scholars also
correlates to their SSCI output
• There is again an ‘English speaking’
bias/benefit

19. Webometrics summary & claims
• Web indicators (content and network) correlate to
other academic performance measures
• Webometrics are regarded as ‘reliable’, but not all
links and content are valid
• Propositions:
– Who links to you is what you are
– Web presence matters for universities and individual
scholars
– Web presence should be part of university’s
institutional strategy

20. A Triple Helix Ranking concept

21. Triple Helix interaction matters for…
• Students & parents: get a job
– For some: become entrepreneurs
• Academics: more money for research
• Companies: better innovation
• Government: happy people and companies
– and innovation eventually grows the tax base

22. Some indicators
• Co-authorship across TH sectors
• Citations of scientific documents in patents
• Mentions of university in industry/government
media/websites (and vice-versa?)
• Production of patents by/with universities
• Number of start-ups from/near the university
• Industry R&D funding
• Employability
• Mobility of researchers across TH sectors

23. Likely pitfalls
• Taking into account local context
– Matters little to students and parents
– Matters to government, local people
• Unintended side-effects of ranking strategies
– Is the Triple Helix a means or an end?
• Too similar to current rankings: nothing new
• Differences between fields
– e.g. theatre vs. electrical engineering
– one size does not fit all

24. The Triple Helix: back to basics
• Three sectors (strands) – industry, university
and government…
– or more? – international, user/consumer
• Co-evolution – through communication
between members of different sectors
• Balance – no single actor is dominant, they lead
together
• Benefits – for all actors involved, and the
innovation ecosystem
• Multiscalar – acts on different scales

25. The Customized Helix-Beyond UIG
• What are the main Helix ‘strands’ in
different sectors?
• Some suggestions:
Theatre Nursing
Engineering
(“traditional” TH)
Actors and writers
Audience
Producers
Government
(censorship, subsidy)
Hospitals & doctors
Patients
Nursing School
Regulator
Companies
Consumers/Users
Universities
Government

26. The Customized Helix
• Even differentiation within fields:
Accounting Marketing Human Resources
Accounting board
Investors
Tax agency
Business school
Firms
Advertising agencies
Consumers
Business school
Labour unions
Firm management
Labour regulation
Business school

27. The role of webometrics
• Provide large-scale quantitative evidence
to understand/confirm cross-sector
interactions taking place
• Versatility in data sources, i.e. goes beyond
patents and academic articles
• Considers both network and content

28. Propositions
1. The strength of the Triple Helix lies in it being
a conceptual model
– What the sectors are, is of secondary importance
2. A Triple Helix ranking can be a hybrid tool for
policy makers, academics and students alike
3. Webometrics is less biased than other
indicators of university quality

29. Time’s up!
• Thank you for participating.
Should you wish to get in touch with us:
• Prof. Han Woo Park – hanpark@ynu.ac.kr,
www.hanpark.net
• Pieter Stek – p.e.stek@tudelft.nl