ECOOM-day, 20 November 2015, Antwerp

Clustering by publication patterns of senior authors in the Social Sciences and Humanities

Frederik Verleysen* & Arie Weeren***ECOOM - University of Antwerp**StatUA - University of Antwerp

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Introduction

Goal: to map diversity in scholarly publication patterns• beyond SS vs. H• beyond disciplines

-> analysis of VABB-SHW data at the author level

Method = Cluster analysis

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Cluster analysis (1)

• = A multivariate technique for classifying similar objects into groups

(authors w/ similar publication patterns = same group)

• Publication patterns of 1828 established authors (>9 weighted publications, >4 years)

• 3 attributes (11 variables) – share per author of:• Publication type (5)• Publication language (2)• Co-authorship (1)

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Cluster Analysis (2)

1. Distance Measure: Mahalanobis distance (Mahalanobis, 1936; Johnson & Wichern, 1992)

• Matrix of dissimilarity between all authors

2. Principal components analysis + Silhouette: • 2-D representation (reduction from 11-D)• 2-cluster solution

3. Partitioning algorithm (K-medoids) (Kaufmann & Rousseeuw, 1990)• Identification of medoids• All objects -> clustered around medoids

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Publication patterns at higher aggregation levels(Engels et al., 2012)

Social Sciences• journal-oriented• WoS and/or Scopus• English• frequent co-authorship

Humanities• importance of book publications• national/regional journals• Regional language (Dutch)• less frequent co-authorship

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Results

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Cluster Labels

Cluster 1• journal-oriented• WoS • English• frequent collaborations-> Cluster 1= Social Scientists?Cluster 2• importance of book publications• national/regional journals• Dutch• less frequent co-authorship-> Cluster 2 = Humanities scholars?

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SS Disciplines in 2 clusters in %Discipline % Cluster 1 % Cluster 2

Criminology 2.5 97.5

Economics 60.5 39.5

Educational Sciences 44.8 55.2

Social Health Sciences 88.1 11.9

Sociology 47.7 52.3

Political Sciences 22.9 77.1

Psychology 90.9 9.1

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H Disciplines in 2 clusters in %Discipline % Cluster 1 % Cluster 2

Archaeology 40.6 59.4

Communication Sciences 25.7 74.3

History 27.2 72.8

History of Arts 37.1 62.9

Law 3.8 96.4

Linguistics 47.1 52.9

Literature 51.6 48.4

Philosophy 47.2 52.8

Theology 18.5 81.5

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Conclusions

• Statistics at disciplinary level hide true diversity in SSH research and publishing

• Sharply contrasting publication patterns of the SS vs. the H is in most cases false

• Method: cluster analysis is promising for application in research evaluation of the SSH. Identification of:

• Units to be assessed• Outputs to be taken into account

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Thank you

Comments & Questions?

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