Node connection strength in PsychTree.
Each node in PsychTree can be characterized by its mean distance from every other node. Below is a histogram of mean distances for every node in the tree. The final bin includes nodes that are not connected to the main tree. Note also that only individuals whose primary affiliation is this tree are included. Nodes cross-listed from other academic trees are included on their primary tree.
Mean inter-node distance|
|Number of nodes|
20 most tightly coupled nodes.
Below are the PsychTree nodes with shortest mean distance.
|1||7.22||Robert C. Honey (Info)||Cardiff University||2010-07-28|
|2||7.69||M. Jackson Marr (Info)||Georgia Institute of Technology||Behavior Analysis||2010-06-08|
|3||8.05||Saul Sternberg (Info)||University of Pennsylvania||Mathematical psychology||2005-03-31|
|4||8.55||Cletus J. Burke (Info)||California State University||mathematical psychology||2009-08-18|
|5||8.61||Evan L. MacLean (Info)||Duke University||comparative psychology, biological anthropology and anatomy||2007-04-26|
|6||8.8||E. Lowell Kelly (Info)||University of Michigan, Ann Arbor||Social Psychology||2009-09-19|
|7||10.77||Brent W. Roberts (Info)||University of Illinois, Urbana-Champaign||personality||2008-09-30|
|8||13.06||Yuka Koremura (Info)||University of North Texas||antecedent control of behavior, generalization, behavioral cusps, fluency-based teaching, treatment of autism, teaching of academic behavior, animal training, rule-governed behavior, contingency-shaped behavior||2015-11-13|
|9||13.35||Richard Russell (Info)||Harvard University||Face perception||2006-10-23|
|10||16.32||John Dewey (Info)||University of Chicago||philosophy, psychology||2005-01-16|
|11||18.85||Tibor P. A. Palfai (Info)||Boston University||Clinical Psychology||2016-06-02|
|12||19.2||G Alan Marlatt (Info)||University of Washington, Seattle||Clinical Psychology, Mental Health||2016-05-19|
|13||21.19||Arthur W. Blume (Info)||University of Washington, Seattle||Clinical Psychology, Public Health||2016-05-20|
|14||21.19||Elizabeth H. Hawkins (Info)||University of Washington, Seattle||Clinical Psychology, Ethnic and Racial Studies||2016-05-20|
|15||21.19||Joseph B. McGlinchey (Info)||University of Washington, Seattle||Clinical Psychology, Educational Psychology Education, Mass Communications||2016-05-20|
|16||21.19||Katie Witkiewitz (Info)||University of New Mexico||Clinical Psychology||2016-05-20|
|17||21.19||Sandra M. Radin (Info)||University of Washington, Seattle||Clinical Psychology, Social Psychology, Developmental Psychology, Public Health, Ethnic and Racial Studies||2016-05-20|
|18||21.19||Neharika Chawla (Info)||University of Washington, Seattle||General Psychology, Public Health||2016-05-20|
|19||21.49||Mary E. Larimer (Info)||University of Washington, Seattle||Addiction||2015-09-19|
|20||32.52||Inna Z. Khazan (Info)||Clark University||Clinical Psychology||2016-05-19|
Distribution of individual connectivity.
Another way to look at the PsychTree graph is to plot a histogram of researchers (nodes) based according to the number of immediate connections (edges) they have to other researchers. The final bin includes nodes with 16 or more connections. The actual distribution has a very long tail, with a maximum of 65 connections. Thanks to Adam Snyder for suggesting this analysis!
Edge vs node distribution|
|Number of connections|