A bibliometric analysis of the interdisciplinary field of cultural evolution

Mason Youngblood1 & David Lahti1,2

1The Graduate Center, City University of New York2Queens College, City University of New York

Introduction

The interdisciplinary study of cultural evolution, or change in socially learned traits over time, has historically been approached from a variety of fields, such as:

• Evolutionary biology• Anthropology• Psychology• Archaeology• Sociology

In the last decade efforts have been made to bridge the historical divisions between these approaches to develop a unified field of cultural evolution (Mesoudi, 2015), but much of this has been based upon subjective perceptions of how the field is structured in terms of collaboration, co-citation, etc. A quantitative analysis of the field would provide valuable information about what parts of field actually require further integration.

Bibliometrics, or the statistical analysis of published materials, has been extensively used to quantify the intellectual structure of fields. In combination with network and cluster analysis, as well as modern data visualization techniques, it can be an invaluable tool for analyzing collaboration and citation patterns (Liu & Xia, 2015; Machado et al., 2015; Sweileh et al., 2016).

The aim of this study was to generate recommendations for future integration of the field of cultural evolution by analyzing co-authorship, citation overlap, and keyword usage in the literature. Co-authorship was chosen as the key metric for the cluster analysis because it is often used as a direct measure of collaboration (Uddin et al., 2011).

Group 1

Group 2

Group 3

Group 4

Group 5

cultural evolutioncultural evolution

cultural evolution

social learning

social learningculture

cultural transmission

cultural transmission

cooperationiterated learning

imitation

evolution

evolution

social learningculture

cultu

ral e

volu

tion

cultural transmission

gene−culture coevolution

language

social learning

cumulative culture

evolution

religionlanguage evolution

cultu

ral a

lgor

ithm

s

evolution

chinaculturesocial learning

cultureinnovation

culture

niche construction

cultural phylogenetics

chimpanzees

evolutionary psychology

tool use

conf

orm

ityhuman evolution innovation

learning

mathematical model

human evolution

phylogeny

cultural algorithm

communicationemulation

chimpanzee

chim

panz

ees

cooperation

demographyevolutionary archaeology

random genetic driftsocial transmission

bird song

diffusion

innovation

dual inheritance theoryforagersphylogenetic comparative methods

bayesian inference

cumulative culture

diffu

sion

cha

in

human evolutionlearning

learning bias

phylogeny

relig

ion

transmission biases

tsimane'

gene−culture coevolution

human evolution

innovation

natu

ral s

elec

tion

random copying

social learning

adaptation

altruism communication

coop

erat

ion

cultural accumulation

evolution

evolutionary game theory

mathematical modelingrelatedness

sexual selection

soci

al

lear

ning

social learning strategy

song

lear

ning

speciation

tradition

cultural transmission

altruismaustronesian

coevolutionlanguage evolutionpunishment

imitation

africa

cultural diversitycultural group selection

evolutionary psychology

hunter−gatherers

kins

hip

phylogenetics

ritual

strong reciprocity

cooperationdifferential evolution

holocene

acculturation

africa

anthropology

boliv

ia

children

cogn

ition

danger

lang

uage

cha

nge

ster

eoty

pes

traditiontraditions

adaptation

agent−based simulation

altruism

animal culturearchaeology

baby names

bromme culture

cladistics

conformity

cultural evolutioncultural learning

discourse

early modern humans

ecology

evol

utio

nary

co

mpu

tatio

n

fashion

game theory

gend

er

handaxes

human culture

imitationindividual learning

individual−based model

insectivory

late glacial

lethal raiding

mar

kets

material culture

narrative

neuroimaging

phylogeny

powe

r law

s

archaeology

bias

consumer behaviorcultural diversity

cultural background

cultural diversity

darw

inis

m

fertility

foraging

groupincest taboo

model

music

song

teac

hing

whale

cross−cultural

development

gender

population genetics

athe

ism

children

cogn

ition

conformism

cultural evolution

cultural norms evolution of cooperation

human evolution

imitation

learning

networksparochialism

prosocialitysocial complexity

soci

al e

volu

tion

supernatural beliefs

chimpanzeescultural heritage

dem

ogra

phy

great apes

individual differences

u−series dating

aggression

alzheimer's disease

ancestral states

ancient dna

anthropology

beha

vior

collective action

collectivismcommunity effects

comparative methodcomputer model

conf

orm

itycostly signaling

cross−culturaldementia

demography

deve

lopm

ent

ethics ethnicity

fairness

fertility

fiji

game theory

institutions

music

norms

prestige

teaching

theory

tool use

tsimane

agriculture

art

cognition

cognitive evolution

cultural evolutioncultural change

geoarchaeology

late pleistocene

learning

multi−objective optimization

neolithic

north china

phylogenyreligion

sustainability

altriciality

anticipation

attraction

bran

d na

rrativ

es

child care

context

croatia

denialemotion

england

fiji

irish

rodinia

798756 745

472 464

338

181 169

11794

0

250

500

750

Num

ber o

f Sha

red

Cite

d R

efer

ence

s

Group1

Group2

Group3

Group4

Group5

04000800012000Number of Cited References

Figure 1. Number of total authors and articles published on the topic of cultural evolution between 1990 and 2015.

Figure 2. Co-authorship network of all authors with a minimum of 100 citations. Five clusters were identified and color-coded using VOSviewer (red: n = 47; green: n = 44; blue: n = 38; yellow: n = 24; violet: n = 24).

Figure 4. Wordcloud depicting keyword frequency among the five groups identified using VOSviewer. Word size corresponds to the frequency of keyword use; word color corresponds to group identity.

Results

Overall collaboration in the field is increasing, as shown by the increased ratio of authors to articles (Fig. 1). Network analysis based on co-authorship showed five distinct clusters of collaboration in the literature (Fig. 2), approximately corresponding to:

• 1 - comparative psychology, evolutionary biology, etc.• 2 - phylogenetics, dual inheritance theory, etc.• 3 - evolutionary psychology, linguistics, etc.• 4 - theoretical biology, animal behavior, etc.• 5 - evolutionary archaeology, anthropology, etc.

Based on the degree in citation overlap (Fig. 3), groups 4 and 5 are the most intellectually isolated from the rest of the field.

Figure 3. Degree of overlap between the cited references of each of the five groups identified with VOSviewer. The dots in the matrix below the bar graph identify which groups are being compared by each bar. The smaller bar graph to the left shows the total number of cited references in each group.

1

2

3

45

Phylogenetics, dual inheritance theory, etc…

Comparative psychology, evolutionary biology, etc…

Theoretical biology, animal behavior, etc…

Evolutionary archaeology, anthropology, etc…

Evolutionary psychology, linguistics, etc…

Dataset & Methods

The complete metadata from every journal article published on the topic of “cultural evolution” on WoS between 1990-2015 was used for this analysis. In total, this included 5753 articles and 11643 authors. VOSviewer and R were used for data analysis and visualization (van Eck & Waltman, 2010).

• Mesoudi, A. (2015). Cultural Evolution: A Review of Theory, Findings and Controversies. Evolutionary Biology, 43(4).

• Liu, P., & Xia, H. (2015). Structure and evolution of co-authorship network in an interdisciplinary research field. Scientometrics, 103(1).

• Machado, R. d. N., Vargas-Quesada, B., & Leta, J. (2015). Intellectual structure in stem cell research: exploring Brazilian scientific articles from 2001 to 2010. Scientometrics, 106(2).

• Sweileh, W. M., Al-Jabi, S. W., Sawalha, A. F., & Zyoud, S. H. (2016). Bibliometric profile of the global scientific research on autism spectrum disorders. SpringerPlus, 5(1480).

• Uddin, S., Hossain, L., Abbasi, A., & Rasmussen, K. (2011). Trend and efficiency analysis of co-authorship network. Scientometrics, 90(2).

• van Eck, N. J., & Waltman, L. (2010). Software survey: VOSviewer, a computer program for bibliometric mapping. Scientometrics, 84.

Number of Authors and Articles by Year

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Year1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010 2012 2014

Art. Auth.

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