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


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