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Tag: social network analysis

Network visualization in R with the igraph package

Published by demetriodor on November 5, 2012

In this post I showed a visualization of the organizational network of my department. Since several people asked for details how the plot has been produced, I will provide the code and some extensions below. The plot has been done entirely in R (2.14.01) with the help of the igraph package. It is a great package but I found the documentation somewhat difficult to use, so hopefully this post can be a helpful introduction to network visualization with R. Here we go: # Load the igraph package (install if needed) require(igraph) # Data format. The data is in ‘edges’ format meaning that each row records a relationship (edge) between two people (vertices). # Additional attributes can be included. Here is an example: # Supervisor Examiner Grade Spec(ialization) # AA BD 6 X # BD CA 8 Y # AA DE 7 Y # … … … … # In this anonymized example, we have data on co-supervision with additional information about grades and specialization. # It is also possible to have the data in a matrix form (see the igraph documentation for details) # Load the data. The data needs to be loaded as a table first: bsk<-read.table(“http://www.dimiter.eu/Data_files/edgesdata3.txt”, sep=’t’, dec=’,’, header=T)#specify the path, separator(tab, comma, …), decimal point symbol, etc. # Transform the table into the required graph format: bsk.network<-graph.data.frame(bsk, directed=F) #the ‘directed’ attribute specifies whether the edges are directed # or equivelent irrespective of the position (1st vs 2nd column). For directed graphs use ‘directed=T’ # Inspect the data:…

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The hidden structure of (academic) organizations

Published by demetriodor on October 23, 2012

All organizations have a ‘deep’ hidden structure based on the social interactions among its members which might or might not coincide with the official formal one. University departments are no exception – if anything, the informal alliances, affinities, and allegiances within academic departments are only too visible and salient. Network analysis provides one way of visualizing and exploring the ‘deep’ organizational structure. In order to learn how to visualize small networks with R, I collected data on the social interactions within my own department and plugged the dataset in R (igraph package) to get the plot below. The figure shows the social network of my institute based on the co-supervision of student dissertations (each Master thesis has a supervisor who selects a so-called ‘second’ reader who reviews the draft and the two supervisors examine the student during the defence). So each link between nodes (people) is based on one joint supervision of a student. The total number of links (edges) is 264 which covers (approximately) all dissertations defended over the last year. In this version of the graph, the people are represented only by numbers but in the full version the actual names of people are plotted, the links are directional, and additional info (like the grade of the thesis) can be incorporated. Altogether, the organization appears surprisingly well-integrated. Most ‘outsiders’ and most weakly-connected ‘islands’ are either occasional external readers, or new colleagues being ‘socialized’ into the organization. Obviously, some people are more ‘central’ in the sense of connecting to a more diverse set of people, while others serve as boundary-spanners reaching…

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New tool for discourse network analysis

Published by demetriodor on April 11, 2012

EJPR has just published an article introducing a new tool for ‘discourse network analysis’. Using the tool, you can measure and visualize political discourses and the networks of actors affiliated to each discourse. One can study the actor congruence networks (based on the number of statements actors share), concept congruence networks (based on whether statements are used by an actor in the same way) and trace the evolution of both over time. Here is a graph taken from the paper which illustrates the actor congruence networks for the issue of software patents in the EU (click to enlarge): The discourse networks analysis tool is free and available from the website of Philip Leifeld, one of the co-authors of the article. I can’t wait to get my hands on the program and try it out for myself. The tool promises to be an interesting alternative to evolutionary factor analysis – another new method for studying policy frames and discourses that I recently discussed – with the added benefit of being able to present actors and frames in an integrated analysis.   Here is the abstract of the EJPR article (there are more resources at this website): In 2005, the European Parliament rejected the directive ‘on the patentability of computer-implemented inventions’, which had been drafted and supported by the European Commission, the Council and well-organised industrial interests, with an overwhelming majority. In this unusual case, a coalition of opponents of software patents prevailed over a strong industry-led coalition. In this article, an explanation is developed based on political…

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