Panel Discussion

  • David M. Blei
Conference paper

DOI: 10.1007/978-3-540-73133-7_17

Volume 4503 of the book series Lecture Notes in Computer Science (LNCS)
Cite this paper as:
Blei D.M. (2007) Panel Discussion. In: Airoldi E., Blei D.M., Fienberg S.E., Goldenberg A., Xing E.P., Zheng A.X. (eds) Statistical Network Analysis: Models, Issues, and New Directions. Lecture Notes in Computer Science, vol 4503. Springer, Berlin, Heidelberg

Abstract

In this volume, we have seen several compelling reasons for the statistical analysis of network data.

  1. 1

    Find statistical regularities in an observed set of relationships between objects. For example, what kinds of patterns are there in the friendships between co-workers?

     
  2. 1

    Understand and make predictions about the specific behavior of certain actors in a domain. For example, who is Jane likely to be friends with given the friendships we know about?

     
  3. 1

    Make predictions about a new actor, having observed other actors and their relationships. For example, when someone new moves to town, what can we predict about his or her relationships to others?

     
  4. 1

    Use network data to make predictions about an actor-specific variable. For example, can we predict the functions of a set of proteins given only the protein-protein interaction data?

     
All of the analysis techniques proposed here are model-based: one defines an underlying joint probability distribution on graphs and considers the observed relationship data under that distribution. Loosely—and this will be a point of discussion among the panelists—the models can be divided into those that are “descriptive” or “discriminative” and those that are “generative.”

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Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • David M. Blei
    • 1
  1. 1.Princeton University, Princeton, NJ 08544USA