University Rankings, thetriple 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
Disclaimer The views expressed in this presentation reflect personal opinionswhich may or may not coincide with the views of the organization with which the authors are affiliated.
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
Agenda Introducing university rankings Webometrics of academia A Triple Helix Ranking concept Debating the pros and cons
University rankings
Which is your favorite?
Rankings compared Criterion QS THE Shanghai Leiden Academic publications, Nobel, Fields Reputation survey 50% 33% Faculty/student ratio 20% 4.5% 20% 36% 90% 100% International 10% 7.5% Other 8.25% (doctor-bachelor ratio) 2.5% (industry income) 8.25% (income) 10% (per capita performan ce)
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.
Alternative: Trojan Condom Ranking
Party School Ranking
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
Webometricsof academia
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]
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
Webometricsrankings? 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
Scholars [C] Online visibility of scholars also correlates to their SSCI output There is again an English speaking bias/benefit
Webometricssummary & 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
A Triple Helix Ranking concept
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
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
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 meansor an end? Too similar to current rankings: nothing new Differences between fields e.g. theatre vs. electrical engineering one size does not fit all
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
The Customized Helix-Beyond UIG What are the main Helix strands in different sectors? Some suggestions: Theatre Actors and writers Audience Producers Government (censorship, subsidy) Nursing Hospitals & doctors Patients Nursing School Regulator Engineering ( traditional TH) Companies Consumers/Users Universities Government
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
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
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. Webometricsis less biased than other indicators of university quality
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