Abstract
Communication decisions in networks can be described as a two-level decision process. The second decision about event receivers is a multinomial logistic regression model with an unknown vector of parameters. These parameters evaluate network structures that enforce or weaken the probability for choosing certain actors. However, in many cases those parameters may change over time. In this paper a sliding window approach is introduced, that can be used to understand whether there is evolution of behavior in an observed data set. For future work, it is proposed to develop a statistical test on normalized decision statistics.
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Stadtfeld, C. (2012). Measuring the Influence of Network Structures on Social Interaction over Time. In: Gaul, W., Geyer-Schulz, A., Schmidt-Thieme, L., Kunze, J. (eds) Challenges at the Interface of Data Analysis, Computer Science, and Optimization. Studies in Classification, Data Analysis, and Knowledge Organization. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-24466-7_32
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DOI: https://doi.org/10.1007/978-3-642-24466-7_32
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