Beyond keywords: A network science approach

to the structure of SPSSI

Kevin Lanning, Fla Atl U

The reciprocal relevance of SPSSI andnetwork science

HistoricalLewin, Heider, Milgram, …

StructuralA languagefor the study of communities

Next U

NY Times, 2/19/2012

Network science can inform the study of inequality

I: Structure

Preferential attachment orthe ‘Matthew Effect’

A common feature of diverse complex social systems

Not just citationsA source of inequality

Network science can inform the study of inequality

II: Content

A pilot analysis32 ASAP papers on “inequality” linked by 1573 references6 research communities

Explorations of the SPSSI citation network

Networks parameters have meaning at five levels of analysis

Level of analysis Concept / parameter Relevance / interpretation

Network (dynamic) Preferential attachment Developmental trajectories of topics, scholars

Network (static) Giant component Connectedness of a research community

Community Modularity Topics, subdisciplines, cliques, categories

Path Diameter, path length Distance and proximity of papers, scholars…

Author/paper (In)degree, centrality Mechanisms of influence, impact, eminence

Bigger data

• All papers published in JSI, ASAP from 2001-2013.• First author, journal, year, cited papers

• N sources = 855• 38854 references(45.4 per source)

• - 2,042 self-references (5.3%)• - 3,198 (8.2%) unusable: references to news articles, government institutes, or

without a date____________________________

• 33,615 usable citations (86.5%)• 24,263 unique papers• 14,702 unique first authors

SPSSI citation network: Connectedness

• Of the 24,263 papers, 24,075 (99.2%) are linked in a single giant component

• Papers are separated by an average of 4.2 links

Eminence and network centrality: 3 interpretations

ID: Citation counts from different sources (in-degree), or total cites (weighted in-degree)

PR (Page Rank, Eigenvector Centrality): Recursive measures in which the importance of a paper is dependent upon the importance of 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.

PageRank is high for papers with commentary• King (2011)

• Second highest PR in database

• Explanation• Papers which are cited by papers with few

references (such as commentaries) can have a disproportionate impact in a sparse network

• Two solutions• Omit commentaries and book reviews • Treat authors rather than papers as the unit of analysis

• Limitations of citation networks: sparseness, time-constraint

The SPSSI author network: (almost) no one is an island• 14,703 unique authors

• All but 6 are linked to the main • Average path between nodes =

5.1

• 32-38 communities*• Average author is linked

1.9 times

Whole network

The SPSSI author

network:Most cited

Includes 68 authors with 20 or more

citations. Nodes ranked by eigenvector

centrality

The SPSSI author network: Centrality

• Content of rankings• Betweenness

(bridging centrality)vs. other measures

Gender effects in citationnetworks?• King (2014): Self-citations• Here, a modest but

possibly consequential effect

Directed Undirectedr (gender, BC-EC) = 0.17 0.22t = 1.70 2.18p (one tailed) 0.05 0.02JSI/ASAP network; analysis includesonly top, bottom 50 in BC-EC (not effect sizes)

The SPSSI author network: Allport and Lewin communities compared

Lewin community includes authors with 5 or more cites; Allport includes authors with 13+ cites. Nodes ranked by eigenvector centrality

(How) has ASAP changed SPSSI?

Total JSI ASAPonly ASAP

unique authors 696 491 233 205unique cited 14568 11704 4848 2864unique scholars (nodes) 14702 11778 4942 2924

Summary, concluding thoughts• Eminence: Great persons and beyond• Centrality: Different measures have distinct interpretations• Connectedness: To see small worlds, you need big data• Communities: Discrete clusters are artificial• Distance: Is more interpretable than proximity• Obsolescence: This work is primitive

• Bigger data and much more sophisticated methods lie ahead

…Safe home

Content: Allport, Pettigrew, Tajfel. But we should resist the temptation to focus only on Great Men, on persons without situations, on the fallacy of independence. As Heather Bullock reminded us in her talk, none of us has built our work alone; as Stephanie Fryberg noted, we need to consider interdependence as well as independent sources of scholarly achievements.CentralitySmall worlds: The law of large numbers applies in how we get to the truth of our connectedness. Giant components and small worlds are more apparent as our data become more complete.Citation networks in personality and social psychology are small worlds in which virtually all of us can be connectedOn articulating the spaceClustering: “Communities” are fuzzy, artificial, and lack robustnessDistance and proximityObsolescencePrimitive: small big data – King studied 1.6 million cites. Others have looked at similar qs in a much more sophisticated way.First authors as opposed to all authorsAuthors as compared with full citationBoyack - more coherent networks can be obtained if one also assesses how far apart they are cited in the source...for example, in the beginning of the introduction or in the methods section.