Network Analytic Techniques for Online Chat

  • Sean P. Goggins
  • Gregory Dyke
Part of the Computer-Supported Collaborative Learning Series book series (CULS, volume 15)


Multivocal analysis applies two or more research methods to the same data set and then applies reflexivity in a joint analysis to achieve greater insights than would be possible with a single method. In this pilot study, we demonstrate how the application of specific methods are influenced by the ordering of the methods, and present a guideline for future multivocal analysis of online chat data using network analytic techniques. We do this in two phases. First, we use Stahl’s ethnomethodological analysis of one session of biology chat discourse to inform decisions about how to identify and weight implicit connections between participants. Implicit connections are useful because they can be easily automated and presented in real time. We then contrast Stahl’s analysis with the networks we derive from those implicit connections, showing some similarities. Second, we use Tatiana to construct ethnomethodologically informed networks for the full corpora and perform network analysis on the resulting explicit connections. The results are not aligned with our first phase analysis of network position and roles for members. Further inquiry illustrates that the session chosen for ethnomethodological analysis by Stahl has different characteristics than the other six sessions, drawing our use of that analysis for building implicit connections in the corpora into question. We conclude with a clear vision for applying the Group Informatics methodological approach to corpora prior to the performance of time consuming qualitative methods like ethnomethodologically informed analysis. Weaving methods together in the right order, we argue, will lead to more rapid and deeper insight.


Automate Analysis Social Network Analysis Knowledge Construction Trace Data Group Informatics 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer Science+Business Media New York 2013

Authors and Affiliations

  • Sean P. Goggins
    • 1
  • Gregory Dyke
    • 2
  1. 1.The University of MissouriColumbiaUSA
  2. 2.University of LyonLyonFrance

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