ECPR Winter School
University of Bamberg, Bamberg
2 - 9 March 2018




WA110 - Introduction to Discourse Network Analysis (DNA)

Instructor Details

Instructor Photo

Philip Leifeld

Institution:
University of Glasgow

Instructor Bio

Philip Leifeld is a senior lecturer (associate professor) in research methods at the University of Glasgow in the School of Social and Political Sciences. His research focuses on social and political networks, quantitative methods, policy debates, and the study of policy processes. His work has been published in the American Journal of Political Science, the Journal of Statistical Software, and elsewhere.


Course Dates and Times

Friday 2 March
13:00-15:00 and 15:30-17:00

Saturday 3 March
11:00-12:00 / 13:00-14:30 and 15:00-16:30

Prerequisite Knowledge

No specific prerequisite knowledge is needed.

Short Outline

In this short course, participants will learn the basics of discourse network analysis, a mixed-methods technique that combines qualitative content analysis with quantitative social network analysis. The approach can be used to study the development of actors and coalitions in policy debates and other kinds of discussions over time based on text data, such as newspaper articles or Congressional testimony. The course will introduce the software Discourse Network Analyzer (DNA) 2.0 and the R package rDNA. Participants will learn how to code statements of actors, how to export networks from the coded data, and how to analyse them in network analysis software such as visone or statnet. The course will introduce the various data transformations and methods available to the user and will discuss ways to get from the initial research idea to a temporal analysis of the discourse network for purposes of description, exploration, and inference.

Long Course Outline

Discourse network analysis is a toolbox of research methods for the analysis of actor-based debates, such as policy debates or political discussions. Examples include the policy debates on climate change, pension politics, or around the introduction of large infrastructure projects. Political actors typically include organisations (interest groups, political parties, government agencies etc.) or individual persons (legislators, celebrities etc.). These actors make statements about policy instruments, solution concepts, narratives, frames, issues, arguments etc. in the media or other arenas, and these statements are temporally and cross-sectionally interdependent. Actors build coalitions in a debate by reinforcing each other’s statements or making similar statements, and they frequently contradict each other over time among these coalitions. The goal of discourse network analysis is to explore, describe, and draw inferences about these processes based on text data and based on a manual qualitative coding in combination with quantitative social network analysis.

The short course will first introduce a few examples from the literature on discourse networks, define the key concepts, and discuss theoretical frameworks that are compatible with the methodological approach of discourse network analysis. We will then consider different text sources, different types of debates, and obstacles in the coding process. The software Discourse Network Analyzer (DNA) 2.0 will be introduced in a hands-on computer lab session, and after demonstrating the coding process in this software, we will proceed with the analysis of the resulting network data in external network analysis software packages, such as visone. The next theoretical block will cover the different export options and algorithms available to the user when exporting network data from DNA. Different data transformations are applicable depending on the type of debate, the nature of the data-generating process, and the goals of the analysis. We will consider, using DNA and network visualisation software like visone, how the choice of the algorithm or method leads to different results, why that is the case, and what method to choose in a given situation. We will also cover basic network analysis techniques that are useful for the analysis of discourse networks (such as community detection algorithms and centrality), and we will briefly consider their implementation in software packages. The course will then proceed by introducing rDNA, which is a package for the statistical computing environment R that permits the user to import network data resulting from DNA directly into R. We will discuss several best practices for doing cluster analysis and other procedures with the data in R, and we will discuss options for the temporal analysis of coalitions and other key features of a debate over time. Finally, we will briefly introduce the statistical or inferential analysis of temporal discourse network data using relational event models for bipartite signed graphs as implemented in the R package rem, and we will discuss the data requirements and theoretical insights to be gained from such an inferential analysis.

The course will be primarily based on lectures and lab tutorials, but participants will be given the opportunity to discuss their own projects and work with their own data in the tutorial lab sessions. To do so, participants should have their text data ready in machine-readable form and bring their own laptops. The course is designed as an introductory short course, but will cover some advanced topics like statistical analysis in R and network analysis in visone. While existing skills in these domains would be an advantage, the course will introduce these skills as far as possible also to a lay audience. To follow the parts that focus on R, however, basic familiarity with R will be required.

Note that this course is neither an introduction to the general principles of qualitative inquiry or content analysis, nor an introduction to quantitative text analysis or machine learning. The focus of the course is specifically on the methodological toolbox of discourse network analysis, from the conceptual stage through manual coding up to inferential network analysis of discourse network data.

Day-to-Day Schedule

Day 
Topic 
Details 
Friday afternoonThe Theory and Methodology of Discourse Network Analysis

Theoretical overview; introduction to network analysis; cross-sectional and longitudinal DNA algorithms and data transformations; empirical examples; data types and management; normalization of discourse networks.

Saturday morningSoftware Lab

Coding and data management in the software Discourse Network Analyzer (DNA); network analysis and visualization with visone; R bindings with the rDNA package; analysis in R.

Saturday afternoonInferential Approaches

Introduction of an agent-based model of political discourse; relational event models for bipartite signed graphs with time-stamped edges and their application to discourse networks.

Day-to-Day Reading List

Day 
Readings 
Friday afternoon
  • Leifeld, Philip (2017): Discourse Network Analysis: Policy Debates as Dynamic Networks. In: Jennifer N. Victor, Mark N. Lubell and Alexander H. Montgomery (editors): The Oxford Handbook of Political Networks. Chapter 12, pages 301-326. Oxford University Press.
  • Leifeld, Philip and Sebastian Haunss (2012): Political Discourse Networks and the Conflict over Software Patents in Europe. European Journal of Political Research 51(3): 382-409.
  • Leifeld, Philip (2013): Reconceptualizing Major Policy Change in the Advocacy Coalition Framework. A Discourse Network Analysis of German Pension Politics. The Policy Studies Journal 41(1): 169-198.
  • Fisher, Dana R., Philip Leifeld and Yoko Iwaki (2013): Mapping the Ideological Networks of American Climate Politics. Climatic Change 116(3): 523-545.
Saturday morning
  • Leifeld, Philip (2016): Policy Debates as Dynamic Networks: German Pension Politics and Privatization Discourse. Frankfurt/New York: Campus. Distributed internationally by the University of Chicago Press.
  • Leifeld, Philip (2017): Discourse Network Analyzer Manual.
  • Rinscheid, A., 2015. Crisis, policy discourse, and major policy change: Exploring the role of subsystem polarization in nuclear energy policymaking. European Policy Analysis, 1(2), pp.34-70.
Saturday afternoon
  • Leifeld, Philip (2014): Polarization of Coalitions in an Agent-Based Model of Political Discourse. Computational Social Networks 1(1): 7.
  • Leifeld, Philip and Laurence Brandenberger (2017): Endogenous Coalition Formation in Policy Debates. Working Paper.
  • Lerner, J., Bussmann, M., Snijders, T. A. B., and Brandes, U. (2013). Modeling frequency and type of interaction in event networks. Corvinus Journal of Sociology and Social Policy, 4:3–32.
Software Requirements

Participants who wish to follow the software lab session should have a recent Java version installed on their laptops (at least Java 8). Java can be downloaded from http://www.java.com. Furthermore, participants should download the most recent versions of the software Discourse Network Analyzer (DNA) 2.0 from https://github.com/leifeld/dna/releases (all files listed under the most recent release version) and the most recent version of visone from http://visone.info/html/download.html (the .jar file, irrespective of operating system). Participants should also install the statistical computing environment R on their laptops, including the latest versions of the packages rJava, rDNA, statnet, and vegan. MacOS users sometimes experience problems with the installation of rJava. In this case, the following tutorial may be helpful: http://charlotte-ngs.github.io/2016/01/MacOsXrJavaProblem.html. All software can be downloaded and used free of charge; some of the software, but not all of it, is also open-source software.

 

Hardware Requirements

Participants are encouraged to bring their own laptops (Windows, Linux, or Mac).

Literature

Brandt, R. 2017. Die optimale Standortwahl von Stromerzeugungsanlagen: Politikwissenschaftliche Analyse von Steuerungsinstrumenten. Baden-Baden: Nomos.

Butts, C. T. 2008. A Relational Event Framework for Social Action. Sociological Methodology, 38(1):155–200.

Butts, C. T. 2008. network: A Package for Managing Relational Data in R. Journal of Statistical Software, 24(2):1–36.

Butts, C T. 2008. Social Network Analysis with sna. Journal of Statistical Software 24(6):1-51.

Fisher, D. R., J. Waggle and P. Leifeld. 2013. Where does Political Polarization Come From? Locating Polarization Within the U.S. Climate Change Debate. American Behavioral Scientist 116(3):523-545.

Goodreau, Steven M., Mark S. Handcock, David R. Hunter, Carter T. Butts and Martina Morris. 2008. A statnet tutorial. Journal of Statistical Software 24(9): 1-26.

Handcock, M. S., Hunter, D. R., Butts, C. T., Goodreau, S. M., and Morris, M. (2008). statnet: Software Tools for the Representation, Visualization, Analysis and Simulation of Network Data. Journal of Statistical Software 24(1):1–11.

Nagel, M. 2015. Polarisierung im politischen Diskurs. Eine Netzwerkanalyse zum Konflikt um “Stuttgart 21”. Berlin: Springer.

The following other ECPR Methods School courses could be useful in combination with this one in a ‘training track .
Recommended Courses Before

Winter School

Introduction to Applied Social Network Analysis

Introduction to R

Recommended Courses After

Summer School

Inferential Network Analysis

Additional Information

Disclaimer

The information contained in this course description form may be subject to subsequent adaptations (e.g. taking into account new developments in the field, specific participant demands, group size etc.). Registered participants will be informed in due time in case of adaptations.

Note from the Academic Convenors

By registering to this course, you certify that you possess the prerequisite knowledge that is requested to be able to follow this course. The instructor will not teach these prerequisite items. If you are not sure if you possess this knowledge to a sufficient level, we suggest you contact the instructor before you proceed with your registration.


Share this page
 

"In all forms of Government the people is the true Legislator" - Edmund Burke


Back to top