Analysing Scientific Collaborations of New Zealand Institutions Using Scopus Bibliometric Data

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Analysing Scientific Collaborations of New Zealand Institutions using Scopus Bibliometric Data

Samin Aref David Friggens Shaun Hendy Department of Computer Science and Ministry of Business Innovation Department of Physics and Te Pūnaha Matatini & Employment, Wellington Te Pūnaha Matatini University of Auckland, New Zealand New Zealand University of Auckland, New Zealand [email protected] [email protected] [email protected]

ABSTRACT ACM Reference format: Scientific collaborations are among the main enablers of Samin Aref, David Friggens, and Shaun Hendy. 2018. Analysing development in small national science systems. Although Scientific Collaborations of New Zealand Institutions using analysing scientific collaborations is a well-established subject Scopus Bibliometric Data. In Proceedings of ACSW 2018: in scientometrics, evaluations of scientific collaborations Australasian Computer Science Week 2018, January 29-February within a country remain speculative with studies based on a 2, 2018, Brisbane, QLD, Australia, 10 pages. limited number of fields or using data too inadequate to be https://doi.org/10.1145/3167918.3167920 representative of collaborations at a national level. This study represents a unique view on the collaborative aspect of 1 INTRODUCTION scientific activities in New Zealand. We perform a quantitative study based on all Scopus publications in all subjects for more There is a growing body of literature that recognises the than 1500 New Zealand institutions over a period of 6 years to importance of scientific collaboration in economic development generate an extensive mapping of scientific collaboration at a [1]. The scientific collaborations can be analysed based on national level. The comparative results reveal the level of bibliometric data using network analysis tools and techniques collaboration between New Zealand institutions and business [2]. The main objective of analysing scientific collaboration is enterprises, government institutions, higher education to gain an understanding of how knowledge flows between providers, and private not for profit organisations in authors [3, 4], institutions [5] and countries [6, 7]. It also helps 2010-2015. Constructing a collaboration network of quantifying research performance measures with a focus on the institutions, we observe a power-law distribution indicating collaborative aspect of research [8]. that a small number of New Zealand institutions account for a Scientific collaboration is seen not only as a performance large proportion of national collaborations. Network centrality measure, but also a representation an entity outreach and concepts are deployed to identify the most central institutions connections to other entities. Some studies focus on of the country in terms of collaboration. We also provide collaborations within a country to compare researchers or comparative results on 15 universities and Crown research institutions and facilitate national research policy development. institutes based on 27 subject classifications. Perc analysed collaboration at the level of individuals in Slovenia [9] and similar study has been undertaken for Turkey CCS CONCEPTS [10]. Collaborations can be investigated between different countries. Park et al. investigated collaborations between China and South Korea using bibliometric data [11]. Nguyen et al. • Information systems → Digital libraries and archives; analysed collaborations of Vietnam with several other countries • Applied computing → Document management and text [12]. processing; • General and reference → Surveys and The university-industry collaboration has been investigated overviews; extensively as an essential connection between institutions of a science system. Abramo et al. investigated the university- KEYWORDS industry collaboration in Italy [13] and found that university arXiv: 1709.02897 v 3 [cs.D L ] 18 Dec 201 7 Big data modelling, Scientific collaboration, Scientometrics, researchers collaborating with industry have a higher research Network analysis, Scopus, New Zealand performance. Investigating collaborations between specific types of institutions in a country usually requires an analysis of research outputs that represent a collaboration tie between the This is an author copy of the paper. The publisher’s verified version of two types of institutions [13]. Yoon and Park investigated the the paper can be accessed on https://doi.org/10.1145/3167918.3167920 collaboration between South Korea universities, industry, and ACM acknowledges that this contribution was authored or co-authored government using network analysis tools and techniques on by an employee, contractor or affiliate of a national government. As patent data [14]. The intermediate step of using network such, the Government retains a nonexclusive, royalty-free right to analysis to study scientific collaboration is evaluating joint publish or reproduce this article, or to allow others to do so, for outputs of authors affiliated with different types of institutions. Government purposes only. Each bibliometric record of such nature represents a visible ACSW 2018, January 30-February 2, 2018, Brisbane, QLD, Australia S. Aref et al.

research connection that can be aggregated for evaluating Auckland, University of Canterbury, and Massey University) collaboration at a national level. have an average level of overall UIC while the other two It is important to point out that three types of collaborations investigated (Victoria University of Wellington and University have long existed in economic development literature and are of Otago) have a medium-low level of overall UIC. These relevant to the role of scientific collaboration; the triadic evaluations are based on a scale of high, medium-high, average, relationship between academia, industry and, the government medium-low, and low UIC in comparison with other is referred to as The Triple Helix. The term was coined by universities listed in 2014 edition of Leiden University Etzkowitz and Leydesdorff [15] to refer to the shift from a Ranking 3 . The overall scores of the five New Zealand dyadic industry-government relationship in an industrial universities across seven disciplines can be found in UIRC 2014 society to a complex hybridisation of elements from academia, report [16]. The report also demonstrates that New Zealand has industry and government in a knowledge society. This shift is a an average overall UIC score which is above Small Advanced result of innovation dynamics that support economic Economies Initiative countries like Singapore and Israel, but development. below Denmark, Switzerland, Finland and Ireland. Note that, The main contribution of this study is quantifying different UIRC 2014 does not include Crown Research Institutes (CRIs), types of scientific collaboration in New Zealand (NZ). This which are government owned research laboratories accounting requires studying co-publications of all pairs of New Zealand for a considerable amount of New Zealand scientific institutions to evaluate the current engagement level between collaborations. Methodological details of UIRC 2014 can be them. Research collaboration among various institutions is found in a study of public–private collaboration [18]. critical to policy development as it facilitates evaluating the current state of collaboration and helps identifying capacities 2.2 SciVal Academic-Corporate metric for improvement in different fields of research. While a few SciVal is a bibliometric analysis service based on the Scopus global studies exist that provide some general observations on data providing research performance of 7500 research New Zealand scientific collaboration, a specific study on New institutions worldwide (at the time of access). SciVal Zealand academia, government and corporations’ collaboration implements the Snowball Metrics [17]; The Academic- has never been undertaken. Following the triple helix concept, Corporate Collaboration Snowball metric is calculated based on we investigate collaboration among all New Zealand Scopus data in 2011-2016. Numerical values for 15 New Zealand institutions that have a publication in a scientific database universities and CRIs range from 0.4% to 1.8% suggesting that within a specified time range. they are comparably active in collaboration with corporations. Note that SciVal’s institutional mapping and classification is not 2 OVERVIEW OF NZ COLLABORATIONS complete. It has better coverage of the larger organisations and Scopus and Web of Science (WoS) are two competing misses many small ones. Notably it only has one commercial bibliometric databases of academic publications. Scopus is NZ institution (Fonterra). The overall Academic-Corporate owned by Elsevier and accompanied by SciVal1 an analytics Collaboration metric for New Zealand is the lowest among service for Scopus data. WoS is maintained by Clarivate Small Advanced Economies Initiative countries. Analytics (formerly Thomson Reuters). In what follows, basic results from Scopus and WoS that are 3 MATERIALS AND METHODS related to New Zealand in comparison to Small Advanced In order to quantify New Zealand research collaborations at Economies Initiative countries2 are discussed: a national level, we consider all New Zealand institutions that 1. University-Industry Research Connections (UIRC) have a publication in Scopus within the six-year time window series of studies [16] based on the WoS data of 2010-2015. We standardise and classify thousands records of 2. An implementation of a snowball metric [17] in SciVal collaborations based on 2010-2015 publications to a list of based on Scopus data institution pairs and their reciprocal number of joint publications4 [19]. 2.1 UIRC Report 2014 We used a full extract of Scopus [20] limiting to NZ The most recent UIRC report [16] uses University-Industry publications between 2010 and 2015 which covers a Co-publication (UIC) as an indicator of scientific performance considerable portion of the scientific publication relevant for in various countries. Using 2009-2012 WoS data, the report our purposes. This was combined with Ministry of Business shows that three New Zealand universities (University of Innovation & Employment (MBIE) internally developed

1 SciVal Elsevier Research Intelligence Solution www.scival.com 3 CWTS Leiden Ranking 2014 www.leidenranking.com/ranking/2014 (accessed on 17/02/2017) (accessed on 17/02/2017)

2 Advanced economies with 5-10 million population including 4 Research data can be accessed at Denmark, Finland, Ireland, Israel, New Zealand, Singapore, and https://doi.org/10.6084/m9.figshare.5705167 Switzerland

Analysing Scientific Collaborations of NZ Institutions ACSW 2018, January 30-February 2, 2018, Brisbane, QLD, Australia

mapping of Scopus Affiliation IDs to NZ institutions. Scopus Finally, the higher education class includes private training uses an automated process to cluster unstructured affiliation establishments, universities, polytechnics, institutes of text and apply its internal Affiliation IDs, but this is technology, independent research organisations, and education conservative and results in multiple IDs per institution. MBIE’s providers classified as wānanga. manually compiled mapping groups together all Affiliation IDs For pairs of collaborating institutions, the collaboration for each NZ institution (for example there are 81 Affiliation IDs records measure equals total number of joint publications. for University of Auckland) and assigns a category (see below). However, when collaboration records are aggregated for a Some affiliations are missing or are not identifiable as specific specific institution, this equality does not hold. Consider a institutions (eg independent researchers), and in some cases publication that has AUT, ESR, and GNS as the affiliations of its there are data errors incorrectly identifying an affiliation as three distinct authors. Such a publication will be counted three being from NZ; these were excluded. Data analysis was times: once as a collaboration record of AUT-ESR, once for ESR- performed using the R language (version 3.4.2) and RStudio GNS, and once for AUT-GNS. Recalling that CRIs and software (version 1.1.383). Gephi version 0.9.1 is used for universities belong to government and higher education network visualisations. categories respectively, when we aggregate the collaborations While UIRC 2014 contains 5 NZ universities and there are of AUT with the government sector, the publication contributes only 37 NZ institutions listed in SciVal (at the time of access), two to the collaboration records between AUT and the our study comprises over 1500 New Zealand institutions. This government sector. study mainly focuses on collaboration measures of 15 New Zealand universities and Crown Research Institutes (CRIs) 4 RESULTS AND DISCUSSION listed below that are expected to account for a large proportion of New Zealand publications in Scopus: 4.1 New Zealand Collaboration Network (1) AgResearch (New Zealand Pastoral Agriculture Research In this subsection, we discuss overall network properties of Institute), (2) AUT University (Auckland University of a scientific collaboration network in which nodes are Technology), (3) ESR (Environmental Sciences Research), (4) institutions and edges represent collaborations between them. GNS Science (the Institute of Geological and Nuclear Sciences), Four institution categories define node types and the (5) Landcare Research, (6) Lincoln University, (7) Massey collaboration records values are used as weights on the edges. University, (8) NIWA (National Institute of Water and The network has 1511 nodes and 4273 edges (network Atmospheric Research), (9) Plant and Food Research (New density is 0.004). Degrees of the nodes follow a power-law Zealand Institute for Plant and Food Research), (10) Scion (New distribution with many institutions having less than 30 Zealand Forest Research Institute Limited), (11) University of collaborators while in the tail distribution a few institutions Auckland, (12) University of Canterbury, (13) University of have hundreds of collaborators. Otago, (14) University of Waikato, and (15) Victoria University Fig. 1 shows a visualization of the network in which size of of Wellington. the nodes are proportional to their weighted degrees. Nodes are We use the numbers in the list above to refer to the 15 coloured respective to their classifications. Business enterprises institutions later in the paper. The key measure to be used is the are shown in red, government institutions in green, higher collaboration record which is the number of joint publications education institutions in blue, and PNP organisations in purple. for pairs of institutions in Scopus within the specified time The network in Fig. 1 is made of one relatively large range. An author with affiliations to two or more institutions is component as well as 21 two-node components and 2 three- not counted as a collaboration. node components representing 23 groups of collaborating We adopt the triple helix concept [15] and use a institutions isolated from the rest of network. classification system with four institution classes. The Like other collaboration networks [3,4], NZ collaboration classification is a mapping between Scopus affiliation IDs, network has the small world property. It has an average standard institution names, and one of the four categories: (1) clustering coefficient of 0.53. For the giant component, the Business enterprise, (2) Private not for profit (PNP), (3) average path length (degree of separation) is 2.75 which much Government, and (4) Higher education. shorter than the network diameter which is 6. Business enterprises are institutions registered in New 66.8% of the institutions in Fig.1 are business enterprises. Zealand Companies Office Register [21]. Proportions for PNPs, government institutions, and higher Private not for profit institutions include institutions education institutions are 18.5%, 11.1%, and 3.6% respectively. classified as building society, charitable trust, contributory The average unweighted degree of the network is 5.66 which mortgage broker, credit union, friendly society, incorporated represents the average number of collaborators for a given society, industrial & provident society, limited partnerships, institution. The average number of collaboration records per other bodies, overseas issuer, participatory security, retirement institution (average weighted degree) is 38.13. villages, superannuation scheme, or unit trust in New Zealand Companies Office other Registers [22]. Government class comprises of Crown Research Institutes, central government institutions, local government institutions, other government institutions, schools, public hospitals, and district health boards.

3 ACSW 2018, January 30-February 2, 2018, Brisbane, QLD, Australia S. Aref et al.

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Jade Software Corporation Orange Consulting Youth Specialty Service Sustainability Society New Zealand Qualifications Authority OTRS Group Ltd New Zealand Stock Exchange Marshall Day Acoustics Ltd. Kiwicap Research Ltd Fabrum Solutions Whisper Tech. Ltd. Southern Obesity Surgery The Life Flight Trust Dunedin City Council Porirua City Council The Correspondence School SUERC Radiocarbon Dating Laboratory Southern Geophysical Ltd Body Aid Clinic Ltd Development Action Ecosynergy Group Ltd (EGL) Lake Hawea Institute of Cryodynamics ENZO Nutraceuticals Limited Opus Research Newman Energy Research Sportsmed John Jones Steel Urology Associates Leinster Orthopaedic Centre Member International Neuropsycholog... Ministry of Justice Akaroa Medical Centre Auckland-Waikato Fish and Game Coun... Western Springs College Air Quality Ltd. Hush Interiors Ltd Toitu Te Whenua Drummond Food Science Advisory Ltd. Assa Abloy New Zealand Ltd DHI Water and Environment Carter National Observatory New Zealand Institute for Plastic a... Canterbury Civil Defence and Emerge... Wellington East Girls College Children's Specialist Centre Tauranga City Council Southern Rehabilitation Institute Te Punaha Matatini Innov8 Group Ltd. Financial Markets Authority Te Arawa Tribal Research Project New Zealand Organisation for Rare D... Rolleston Medical Centre Spotswood College New Zealand Antarctic Institute Animation Research Limited NZ Parsa Tiling Limited Health Care Aotearoa Whatever It Takes (WIT) The Breast Centre Ferndale School Colgate-Palmolive Ltd Midwifery Council of New Zealand Clinical Horizons Kiwi Well Evaluation Ltd Duncan Cotterill Wellington Regional Plastic Central Otago Tourism Aviation Industry Association of Ne... 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New Zealand Society for Earthquake ... Dobbie Engineers Ltd.

Figure 1: New Zealand Scientific collaboration network visualised as a weighted network (image credit © Samin Aref)

4 Analysing Scientific Collaborations of NZ Institutions ACSW 2018, January 30-February 2, 2018, Brisbane, QLD, Australia

4.2 Induced Subgraphs of Crown Research Institutes In what follows, smaller parts of the network, commonly referred to as ego networks, are illustrated. Ego networks are induced subgraphs of neighbours centered at a specific node. Figs. 2-8 represent the induced subgraphs of 7 CRIs and their collaborators. Each induced subgraph represents the main institution located in the centre with a distinctive node size. The other nodes represent the collaborating institutions that are all connected to the central node and coloured respective to the classification. Thickness of the edges is proportional to the number of joint publications between the collaborating institutions. Business enterprises are shown in red, government institutions in green, higher education institutions in blue, and PNP organisations in purple. From the induced subgraph in Fig. 2 we observe that AgResearch has strong collaboration ties to higher education Figure 3: ESR induced subgraph institutions. There are many business enterprises collaborating with AgResearch as shown in Fig. 2. The ESR induced subgraph shows strong collaboration ties to higher education institutions. There are only a few collaborating PNPs in the induced subgraph of ESR in Fig. 3, while government category seems to account for many ESR collaborators. Like subgraphs of AgResearch and ESR, GNS Science induced subgraph and that of Landcare Research show strong collaboration ties to higher education institutions. Fig. 4 shows that a few PNPs collaborate with GNS Science, while many PNPs have collaboration with Landcare Research as illustrated in Fig. 5.

Figure 4: GNS Science induced subgraph

Figure 2: AgResearch induced subgraph

Figure 5: Landcare Research induced subgraph

5 ACSW 2018, January 30-February 2, 2018, Brisbane, QLD, Australia S. Aref et al.

Fig. 6 indicates that NIWA collaborates with all four types of institutions and most actively with higher education institutions. There are many PNPs collaborating with NIWA compared to other CRIs. Fig. 7 demonstrates relatively many business enterprises collaborating with Plant and Food Research. Strong ties to higher education institutions are visible for Plant and Food Research induced subgraph. The number of Scion collaborators is less than most other CRIs as evident in Fig. 8 which only shows one PNP collaborator.

Figure 8: Scion induced subgraph

4.3 Centrality Analysis of the Network The rest of this Section provides quantitative results on two centrality analyses that determine the most central institutions of the network. Considering New Zealand collaboration network as a map representing the connections between institutions, it would be insightful to find the most important nodes of the network [22,23]. Betweenness [23] and eigenvector centrality [24] are standard network analysis tools that provide a quantitative

Figure 6: NIWA induced subgraph measure of centrality for nodes of a given network. Betweenness centrality captures the importance of a node in a network based on its role of connecting other nodes. It measures how often a specific node appears on a path between two other nodes [23]. Eigenvector centrality contains an aggregate of a node’s degree and its neighbours’ degrees summed up based on a decreasing weight of distance to the neighbour [24]. Figs. 9-10 show ten most central institutions based on betweenness and eigenvector centrality measures respectively.

Figure 7: Plant and Food Research induced subgraph

Figure 9: Central institutions based on betweenness centrality

Analysing Scientific Collaborations of NZ Institutions ACSW 2018, January 30-February 2, 2018, Brisbane, QLD, Australia

Wellington. This order corresponds to the five largest nodes in Fig. 1 (recall that, the collaboration record counts equal weighted degrees of the nodes).

Figure 10: Central institutions based on eigenvector centrality Figure 11: Collaboration records proportions for 15 The most striking observation to emerge from Figs. 9-10 is universities and Crown research institutes that not all NZ universities are among the 10 most central institutions in terms of collaboration. Instead some district health boards and CRIs can be seen in Figs. 9-10. Recall that in Fig. 1, the eight universities were not exactly the eight largest nodes of the network. This means that based on degree centrality, some district health boards and CRIs are more central than some NZ universities.

5 COLLABORATION RATIOS In this Section, we analyse the ratios of collaboration for each of the 15 universities and CRIs. This section can be considered as an analysis of weighted degrees of the nodes. The collaboration ratios are provided as proportions in Fig. 11 and total counts in Fig. 12. Numbers on the vertical axis refer Figure 12: Collaboration records counts for 15 to the 15 universities and CRIs as listed in Section 3. Purple, universities and Crown research institutes blue, green, and red colours in Figs. 11-12 represent collaboration with PNPs, higher education providers, 6 CONCLUSIONS government institutions, and business enterprises respectively. This study investigated research collaborations among New Three faceted plots based on All Science Journal Zealand institutions based on all Scopus publications from 2010 5 Classification (ASJC) are provided in the appendix. They can to 2015. Research collaborations were quantified by numerical be used for comparing scientific collaborations in different measures based on joint publications of New Zealand fields of research as well as comparing universities and CRIs institutions. based on their collaboration records in each ASJC subject. We have considered four classifications for the institutions, A comparison of relative collaborations with the four namely higher education, government, business enterprise, and institution categories can be made based on Fig. 11. Lincoln private not for profit. The raw data containing thousands of university (6) has the highest proportion of collaboration with Scopus affiliation IDs was categorised into standard institution government. Regarding collaboration with business enterprises, names and classes defining nodes of a scientific collaboration Scion (10) has the highest proportion. University of Canterbury network where collaborations are represented by weighted (12) has the highest proportion of collaboration with PNPs. edges. The network is unique in its representative capability for Fig. 12 shows that University of Auckland has the highest research collaborations at a national level. collaboration count followed by University of Otago, Massey University, University of Canterbury, and Victoria University of

5 A journal subject classification including 1 general and 26 specific Sciences, Economics Econometrics and Finance, Energy, Engineering, subject classes: Agricultural and Biological Sciences, Arts and Environmental Science, Health Professions, Immunology and Humanities, Biochemistry Genetics and Molecular Biology, Business Microbiology, Materials Science, Mathematics, Medicine, Neuroscience, Management and Accounting, Chemical Engineering, Chemistry, Nursing, Pharmacology Toxicology and Pharmaceutics, Physics and Computer Science, Decision Sciences, Dentistry, Earth and Planetary Astronomy, Psychology, Social Sciences, and Veterinary.

7 ACSW 2018, January 30-February 2, 2018, Brisbane, QLD, Australia S. Aref et al.

The centrality analysis, demonstrated in Figs. 9-10, indicated [3] Newman, M. E. The structure of scientific collaboration networks. Proceedings of the National Academy of Sciences, 98, 2 (2001), 404-409. the most central institutions in terms of scientific collaboration. The quantitative results on collaboration records, illustrated in [4] Barabási, A. L., Jeong, H., Néda, Z., Ravasz, E., Schubert, A. and Vicsek, T. Figs. 11-12, shed light on collaborations between New Zealand Evolution of the social network of scientific collaborations. Physica A: Statistical Mechanics and its Applications, 311, 3–4 (2002), 590-614. universities/CRIs and different types of institutions at a national level. We have also used ASJC subjects to analyse [5] Katz, J. Geographical proximity and scientific collaboration. Scientometrics, 31, 1 (1994), 31-43. research collaborations in 27 different fields of research whose comparative results can be found in the Appendix. It would be [6] Gazni, A., Sugimoto, C. R. and Didegah, F. Mapping world scientific collaboration: Authors, institutions, and countries. Journal of the American insightful as a future research to investigate whether the same Society for Information Science and Technology, 63, 2 (2012), 323-335. observations, including the centrality analysis, hold true if other sources of bibliometric data are used. [7] Luukkonen, T., Tijssen, R., Persson, O. and Sivertsen, G. The measurement of international scientific collaboration. Scientometrics, 28, 1 (1993), 15-36. While we focused on 15 universities and CRIs in New Zealand, the analysis was performed for over 1500 New Zealand [8] Abbasi, A. and Altmann, J. On the Correlation between Research Performance and Social Network Analysis Measures Applied to Research Collaboration Networks. institutions comprising of business enterprises, charitable City, 2011. trusts, union trusts, incorporated societies, and limited partnerships registered in New Zealand companies office [9] Perc, M. Growth and structure of Slovenia’s scientific collaboration network. Journal of Informetrics, 4, 4 (2010), 475-482. register as well as central and local government institutions, schools, district health boards, private training establishments, [10] Çavuşoğlu, A. and Türker, İ. Scientific collaboration network of Turkey. Chaos, Solitons & Fractals, 57 (2013), 9-18. polytechnics, institutes of technology, and independent research organisations. [11] Park, H. W., Yoon, J. and Leydesdorff, L. The normalization of co-authorship This research has opened many avenues to be explored by networks in the bibliometric evaluation: the government stimulation programs of China and Korea. Scientometrics, 109, 2 (2016), 1017-1036. more in-depth analysis on New Zealand bibliometric data. For one research direction, the analysis can be extended allowing [12] Nguyen, T. V., Ho-Le, T. P. and Le, U. V. International collaboration in scientific research in Vietnam: an analysis of patterns and impact. Scientometrics, for measures of research quality to play a role in evaluating 110, 2 (2017), 1035-1051. collaborations. Field-normalised citation based measures [25] [13] Abramo, G., D’Angelo, C. A., Di Costa, F. and Solazzi, M. University– might be suitable candidates to be used as measures of research industry collaboration in Italy: A bibliometric examination. Technovation, 29, 6–7 quality. Evaluating the potential improvement capacities across (2009), 498-507. different disciplines would be another direction that can be [14] Yoon, J. and Park, H. W. Triple helix dynamics of South Korea’s innovation taken from a policy development perspective. Observing a few system: a network analysis of inter-regional technological collaborations. institutions accounting for a large proportion of collaboration Quality & Quantity, 51, 3 (2017), 989-1007. and most of the results confirming intuitive expectations, a [15] Etzkowitz, H. and Leydesdorff, L. The Triple Helix--University-industry- third recommendation for future work is incorporating a government relations: A laboratory for knowledge based economic development measure of institution size to get the relevant measures per (1995). capita and use them for a better comparison of research [16] Leiden University CWTS University-Industry Research Connections., 2014. collaboration performance of the institutions. www.cwts.nl/UIRC2014 (accessed on 17/02/2017) [17] Colledge, L. Snowball metrics recipe book. Amsterdam: Snowball Metrics ACKNOWLEDGMENTS Program Partners (2014). Andrew Marriott and Sam Holmes at Ministry of Business [18] Tijssen, R. J. Co-authored research publications and strategic analysis of Innovation & Employment (MBIE) performed much of the work public–private collaboration. Research Evaluation (2012). classifying New Zealand institutions. The first author would [19] Aref, S., Friggens, D. and Hendy, S. Network of scientific collaborations like to thank Peter Ellis and Franz Smith for their support. This between New Zealand institutions based on Scopus publications from 2010 to 2015. figshare (2017). DOI 10.6084/m9.figshare.5705167 work was partially supported by the following sources: - Te Pūnaha Matatini 2016-2017 postgraduate internship [20] Elsevier. Scopus Custom Data extracted June 2016. program at Ministry of Business, Innovation & Employment [21] NZCO New Zealand Companies Office Register. New Zealand, 2017. - The Computing Research and Education Association of Australasia partial support grant (CORE Student Travel Award) [22] NZCO New Zealand Companies Office Other Registers. New Zealand, 2017. - Callaghan Innovation grant number 9152 3705825 [23] Freeman, L. C. Centrality in social networks conceptual clarification. Social networks, 1, 3 (1978), 215-239. [24] Bonacich, P. Factoring and weighting approaches to status scores and clique REFERENCES identification. Journal of Mathematical Sociology, 2, 1 (1972), 113-120. [25] Waltman, L. A review of the literature on citation impact indicators. Journal of Informetrics, 10, 2 (2016), 365-391. [1] Sonnenwald, D. H. Scientific collaboration. Annual review of information science and technology, 41, 1 (2007), 643-681.

[2] Fung, H.-N. and Wong, C.-Y. Scientific collaboration in indigenous knowledge in context: Insights from publication and co-publication network analysis. Technological Forecasting and Social Change, 117 (2017), 57-69.

Analysing Scientific Collaborations of NZ Institutions ACSW 2018, January 30-February 2, 2018, Brisbane, QLD, Australia

A APPENDIX

Collaboration records count within New Zealand for each ASJC fields

ACSW 2018, January 30-February 2, 2018, Brisbane, QLD, Australia S. Aref et al.

Comparison of collaboration records of 8 New Zealand universities based on ASJC field

Comparison of collaboration records of 7 Crown research institutes based on ASJC field