Analyses of the structure of social-personality psychology as manifest in bibliometric couplings within the Journal of Personality and Social Psychology for selected years between 1981 and 2014

1. The structure of (personality and)
social psychology:
An empirical investigation
using social network analysis
Kevin Lanning
SPSP social dynamics preconference
Long Beach, CA
February 2015
Slides posted at
www.slideshare.net/lanningk/JPSPstructure2015

2. Overview
•Networks, citations, bibliometrics
•JPSP and the structure of social (&,/,- personality)
psychology
•Foretelling which papers will get cited
•Communities and the category structure of
scholarship
• (omitted from presentation due to time constraints)
•The problem of Big Data Reduction

3. Networks
citations
bibliometrics

4. Why networks?
•Community as a level of analysis
•The reciprocal relevance of social psychology and
network science
•Historical: Lewin, Heider, Milgram, …
•Contemporary: Inequality in complex systems
•The power of empiricism
•The availability of new tools for network analysis

5. Why scholarly networks?
• Science as a social endeavor
• A citation is a dyadic, directed act which occurs in a
cultural context
• The need for a better map of scholarship
• From arbitrary keywords
to a tool for fostering
social and intellectual
capital

6. Levels of analysis in citation networks
Level of analysis Concept / parameter Relevance / interpretation
Network (dynamic)
Preferential
attachment
Developmental trajectories of
topics, scholars
Network (static)
Giant component,
density
Connectedness of a research
area
Community Modules, cliques
Topics, subdisciplines,
categories
Path
Diameter, path
length
Distance and proximity of
nodes
Node: Author, paper,
journal, department Degree, centrality
Forms of influence, impact,
eminence

7. Two types of scholarly network
The citation network
• Source -> Reference
• Directed, biphasic,
large, sparse
… here, a loss of older
(no doi) cites
The structural network
• Source <-> Source
• Bibliometric couplings
• Undirected, single mode, small, dense
Smith,
2014
Thomas,
2014
Abe, 2011 Baker, 1971 Coe, 2009 Davis, 1999
Reed,
2014
Smith,
2014
Thomas,
2014
Abe, 2011 Coe, 2009 Davis, 1999
Reed,
2014
Reed,
2014
Smith,
2014
Thomas,
2014

8. JPSP
andthestructure
ofsocial...personality

9. How many tribes in social-personality psychology?
‘SSP’
A singular social psychology
‘SPSP’
At the very least, an ‘&’ rather than a ‘/’ or ‘-’
‘SAIPP’
The three sections of JPSP as a valid model
Weak vs. strong forms of hypothesis.
Method
Develop and examine JPSP 2014 structural network
nb: The procedure for culling references from PsycInfo is posted at
https://github.com/kevinlanning/StructureOfSocialPsychology/blob/master/ParsefromPsycInfo.Rmd

10. Properties of the JPSP 2014 -> reference
(citation) network
Biphasic, directed
6159 Nodes
• 118 articles
• 10024 citations
• 7248 with doi
• 6041 unique references
(cited in 1 or more papers)
7248 Edges
• Sparse: Density rounds to 0 (7248/(6159 * 6158))
Average path = 3.7, diameter is 6 (undirected)
All articles are linked in a giant component

11. Results from the citation network:
Papers most frequently cited in JPSP 2014
cites reference
19 Preacher, K. J. Hayes, A. F. (2008). … indirect effects in ... mediator models. BRM, 40, 879-891.
14
Buhrmester, M. Kwang, T. Gosling, S. D. (2011). Amazon's Mechanical Turk. Pers. Psych Sci, 6, 3-
5.
13
Blanz, M. (1999). Accessibility & fit determine salience of social categoriz. EJ Social Psych, 29,
43-74
10
Baumeister, R. F. Leary, M. R. (1995). The need to belong: attachments … Psych Bull, 117, 497-
529.
10
Altemeyer, B. (1998). The other “authoritarian personality”. In M. Zanna (Ed.), Adv in Exper. Soc
Psy. .
10
Simmons, J. P. Nelson, L. D. Simonsohn, U. (2011). False-positive psychology Psych Sci, 22, 1359-
66.
9
Franco, F. M. Maass, A. (1999). Intentional control over prejudice: When the choice of the measure matters. European Journal of Social
Psychology, 29, 469-477.
9 Watson, D. Clark, L. A. Tellegen, A. (1988). The PANAS Scales. JPSP, 54, 1063-1070.
8 Preacher, K. J. Hayes, A. F. (2004). SPSS and SAS … mediation models, BRM, 36, 717-731.
8 Shiner, R. Caspi, A. Goldberg, L. R. (2007). The power of personality. Pers. on Psych Sci, 2, 313-345.

12. Properties of the JPSP <-> JPSP
structural network
Single mode, undirected, small
118 Nodes (articles)
1421 Edges
Edges are weighted by number of
common citations
The network is dense
The average paper is directly linked to 24 others
(20.6% of all possible links)
Average path is 1.9, diameter is 4

13. Connections within/between JPSP sections
JPSP Section(s) Papers
(nodes)
Edges Density Density between
sections
Attitudes 30 170 39.1% --
Interpersonal 43 243 26.9 --
Personality 45 241 24.3 --
Attitudes & Interpers 73 686 26.1 21.2
Attitudes & Personality 75 605 21.8 14.4
Interpers & Personality 88 784 20.5 15.5
All sections 118 1421 20.6 16.8
Greater density within than between sections: The typical ‘Attitudes’ paper
shares refs with ~ 40% of papers in Attitudes, ~ 20% in the other sections

14. So what?
• Relative homogeneity provides support for the weak form
of validity of the three areas
• But unclear just how distinct the areas are

15. A longitudinal approach
• Are the three areas, or personality and social, growing
more separate?
• Method
• Analysis of 1981*, 1994, 1999, 2004, 2009 and 2014
volumes
• Comparison of citations within areas to citations
between areas over time

16. JPSP connectedness over time: Detail
1981 1994 1999 2004 2009 2014
w/in Attitudes 11.5% 21.0% 30.9% 27.8% 21.9% 39.1%
Interpersonal 2.9% 6.5% 15.8% 24.1% 20.1% 26.9%
Personality 4.6% 16.4% 14.1% 15.2% 19.8% 24.3%
bet A & I 2.0% 7.2% 14.7% 19.6% 16.1% 21.2%
A & P 3.4% 6.4% 11.3% 6.5% 12.0% 14.4%
I & P 1.9% 7.1% 9.8% 9.3% 12.9% 15.5%
The Attitudes and Interpersonal sections are closer to each other
than either is to the Personality section

17. JPSP connectedness over time: Summary
1981 1994 1999 2004 2009 2014
Within sections 6% 16.3% 17.3% 22.4% 20.4% 28%
Between 2.7% 6.8% 11.4% 11.4% 13.6% 16.8%
Within/between 2.3 2.4 1.5 2.0 1.5 1.7
in 2014, a paper in JPSP was ~ 70% more likely to share
a reference with a paper in the same section than in
one of the other sections

18. JPSP connectedness over time:
‘Controlling’ for network size
1981 1994 1999 2004 2009 2014
N edges 2879 4938 4551 4761 6880 7248
Within/between 2.3 2.39 1.52 1.95 1.49 1.68
N selected edges 4547 4551 4550 4551 4547
Within/between 2.44 1.52 2.02 1.52 1.70
Relative homogeneity of discrete areas holds up
after randomly slicing ~ 35% of references.

19. Foretelling
futurecitations

20. Predicting citations
•Does the location of a paper in a network
predict future citations?
•Concepts of network centrality
•A second use of the longitudinal data
•Prospective analyses
•1994, 1999, 2004, 2009 properties ->
citations to 2014

21. Different forms of network
centrality
Degree and weighted degree: Number of
direct links, possibly weighted by total
shared cites
PR (Page Rank, Eigenvector Centrality):
Recursive measures in which the
importance of a paper is dependent upon
the importance of the papers which refer to
it
BC (Betweenness Centrality): Extent to which a
node bridges different areas of scholarship,
introduces work to a new audience, etc.

22. Most central papers in JPSP 2014 on 3 metrics
Id source.title BC WD PR
Rauthmann_J.p.107.677 The Situational Eight DIAMONDS 1 3 1
Gebauer_J.p.107.1064 Cross-cultural variations in Big Five r religiosity 2 2 7
Wakslak_C.a.107.41 Using abstract language signals power. 3 11 2
Barasch_A.a.107.393 Selfish or selfless? On the signal value of emotion in altruism 4 18 9
McClure_M.i.106.89 …attachment anxiety hurts relational opportunities. 5 7 4
Frimer_J.i.106.790 Moral actor, selfish agent. 8 13 5
Dunning_D.i.107.122 Trust at 0 acquaintance: respect not expectation of reward. 9 9 3
Lemay_Jr._E.i.106.37
Diminishing self-disclosure to maintain security in partners'
care. 16 1 8
Lemay_Jr._E.i.107.638
Accuracy/bias in self-perceived responsiveness -> security in
romantic rs. 18 5 22
Hui_C.i.106.546
When relationship commitment fails to promote partners'
interests. 24 3 16

23. Nodes graded by Betweenness, Weighted
degree, and (unweighted) PageRank

24. Node properties -> future cites:
correlations and regression coefficients
1994 1999 2004 2009 across years
year -- -- -- -- -0.28
nrefs 0.2 0.24 0.18 0.2 0.14
PageRank 0.22 0.24 0.24 0.22 0.17
Betweenness 0.15 0.18 0.05 0.15 0.12
Degree 0.22 0.21 0.18 0.22 0.12
year -- -- -- -- -0.06
nrefs 0.16 0.19 0.14 0.16 0.16
PageRank 0.17 0.23 0.32 0.17 0.20
Betweenness -0.18 -0.10 -0.24 -0.18 -0.10
Degree 0.15 0.00 0.05 0.15 0.01
R2 0.08 0.08 0.10 0.08 0.14
Adjusted R2 0.05 0.06 0.07 0.05 0.13

25. Communities
andthecategory
structureofscholarship*

26. The challenge of communities
Partitioning a continuous universe
Three approaches
• A priori
• Three JPSP areas
• Top down (divisive)
• Modularity assessment of whole graph
• All inclusive, too Procrustean
• Bottom up (agglomerative)
• Begin with cliques
• May allow for overlapping categories
• Not all inclusive, may be too selective

27. Modularity analyses of JPSP 2014
• Results not robust
• Number of communities is dependent upon random seed
• A 7 community solution is representative
• 2 primarily attitudes
• 2 primarily interpersonal
• 1 personality
• 2 mixed
Community Att Int Pers
I 7 2 0
II 10 2 1
III 0 16 2
IV 4 10 3
V 0 2 26
VI 4 2 3
VII 5 9 10

28. Modularity in SPSSI
journals: Allport & Lewin
Lewin community includes authors with 5 or
more cites; Allport includes authors with 13+
cites. Nodes ranked by eigenvector centrality

29. A complex systems view
(Palla et al, 2005)
Communities as cliques
• Each node is linked to
at least k other nodes
• Family resemblance
Nodes (papers) may belong
to multiple communities
Overlapping communities
also constitute a network
• Multiple levels of
categorization
Open source software at Cfinder.org

30. Exploring community structure
in the JPSP 2014 data
• Explore thresholds for filtering data
• Here, minimum edge weight of 2
• Investigate network structure for various
values of k
• Here, k > = 5
• Communities are groups in which each paper is connected
by at least 2 common citations to at least 4 other papers within
the community
• Here, 8 communities in two separate components

31. Cinder
Personality
Pers’y & relationships
Interpersonal processes
Mixed

32. Cinder
Attitudes
Attitudes
Mixed
Mixed
Personality

33. Theproblem
ofBigDataReduction

34. On data visualizations

35. Same data, two different formats
JPSP 2014 structural network. Node size f(PageRank), degree >= 30. Spline
applied in right panel.

36. Big Data requires Big Data reduction
many ‘truths’ can be told
non-arbitrary principles for constructing data
visualizations are needed