Friday, November 6, 2015

Advocating for the Use of Social Network Analysis in Individual Psychology

Curlette, W. L., & Hendrick, R. C. (2015). Advocating for the Use of Social Network Analysis in Individual Psychology. The Journal of Individual Psychology, 71(1), 75-85.

The primary focus of this article is to show the potential social network analysis has in the field of Individual Psychology.  The article states that research employing quantitative methods for social network analysis in Individual Psychology has not been published in The Journal of Individual Psychology, and that it is unlikely social network analysis work has been published in any other journal in the field either.  They cite the University of Twente website when describing social network analysis, Network analysis (social network theory) is the study of how the social structure of relationships around a person, group, or organization affects beliefs or behaviors.  The authors also state that, although social network analysis focuses on relationships between actors, characteristics of actors in the network can be related statistically to measures of the network.

The quantitative methodology laid out by the authors as a general example of social network analysis starts with a questionnaire given to the group in question.  Based on the responses to that questionnaire, in regards to the frequency and nature of their relationships with others, a square matrix can be generated.  This matrix will show in numeric terms who is communicating in the group being examined.  The specificity of the information in the matrix can be improved by carefully shaping the questions on the survey to take into consideration the characteristics of the people on the list, examples are what organization they work for or what country they are from.  The authors believe that an area for the application of social network analysis in Individual Psychology is the study of Gemeinschaftsgefuhl, which has been translated as "social interest". 

The section “Data Analysis for the Social Networks” provides a good overview of social network analysis.  It refers back to the matrix that was mentioned earlier and how it allows for the creation of dichotomous responses as well as the frequency or strength of communication.  Eight measure are employed for describing social networks:
  1. Size of the matrix – number of rows or number of columns
  2. Density – there are various definitions, including number of ties in matrix of dichotomous responses as a proportion of total number of possible ties
  3. Reciprocity - proportion of actors selecting one another, with the highest possible value being 1.0
  4. Transitivity - relationships between triads of actors, which can indicate the degree of stability and consistency of the network
  5. Diameter - number of steps in the longest path connecting two actors, which can indicate how resources are transferred
  6. Distance - mean path length between all pairs of actors
  7. Clustering - areas of dense connections between actors
  8. Centralization - high centralization occurs when a small number of actors are the focus of many relations, which indicates both how resources are distributed across the network and a high concentration of power and control

Comparing two networks can be done descriptively or by using the Quadratic Assignment Procedure (QAP).  The QAP is a resampling approach using Monte Carlo methods.

The best example given in the article involved the analysis of HIV and HPV research on an international scale.  The countries in which the research was published are the nodes and all the information was presented as a graph.  The US had the most research, therefore the USA node is the largest.  The width of the connections indicates the number of collaborations between any two countries.  This is just one example, the nodes could easily be organizations, schools, or families.


From the prospective of trying to educate an unfamiliar audience with the possibilities and capabilities of social network analysis this article is very successful.  The underlying principles of social network analysis were laid out in the methodical and easy to read format.  In terms of adding to the overall field of Individual Psychology this article does little.  All that is really accomplished by the authors is that they have shown that social network analysis is a methodology which will work with Individual Psychology, and provide a few examples of analysis that could potentially be done.  


  1. Dan, I agree with your assessment of the article. It makes SNA easy to understand, while mainly describing its potential uses. I also liked the list of the various ways to describe social networks since the correct perspective to looking at results is key to analysis and understanding.

  2. The authors make a point about the characteristics of actors within the network. I think this topic could yield interesting research examining how social networks develop, particularly within organizations. This could also be an explaining factor between formal and informal network analyses.

  3. Dan, I think what makes a person a powerful center node is highly related with the characteristics of that person. In this article too, I see it mentions about this characteristic issue. I was going to ask whether the study detail how to quantify a characteristic feature of an individual and apply it to the SNA?