Chaotic behavior in computer mediated network communication

Abstract

The work examines the use of chaos theory in modelling time series data generated by computer mediated communication (CMC). Data generated by CMC bulletin boards is examined for the presence of chaotic behavior and to assess the variance which can be accounted for by the deterministic mechanism. The study regards the time series data generated from a CMC discussion group as the sum of two components. One is a deterministic “signal” which presumably obeys some unknown chaotic dynamics. The other component is truly random “noise”. The study's overall goal is to assess the relative importance of these two components, using techniques devised by Procaccia and Grassberger for studying chaos in time series data. Chaotic time series data had increasingly larger fractions of noise added until chaotic behavior was no longer found. Analysis of the data with added noise indicates that from 20 to 30% of the variation in the data is the result of noise. Conversely, 70 to 80% of the variation in the data can be accounted for by deterministic chaos. Implications for future research using chaos and CMC are discussed.