(Page 2 of 26) - A Conditional Probability Analysis of Pattern-Based Models Applied to Event Data in the Israeli-Palestinian Conflict authored by Schrodt, Philip. and Hudson, Valerie.

Schrodt and Hudson

Page 1

Introduction and Background

In 2002, a methodological gauntlet was thrown down by Stephen Wolfram in his work, A New Kind
of Science. Though his book was not written from or for a social science perspective, several of his
assertions are pertinent to that endeavor. Wolfram asserts that most modern scientific methods used
in the physical and biological sciences are but idiosyncratic and limited derivations from something
much more basic, more fundamental, and more powerful. In place of the continuous-variable
mathematical structures that underlie classical mechanics and statistics, Wolfram's approach focuses
on the discrete transformation of patterns. Simple pattern-based models can, through iteration,
produce surprisingly complex behavior in physical and biological systems. Biochemists, for
example, search for patterns in amino acids as elements for understanding the functions of a strand
of DNA, and then the patterns of those strands combine to produce the patterns formed by larger
strands, then by chromosomes, then by the entire genome. Though the patterns themselves are
simple, they can ultimately produce highly complex organisms, including human beings themselves.

Conveniently for social scientists, humans do not only originate from patterns, but human
psychology is intensely linked to the ability to perceive patterns and to find meaning in patterns
(Newell and Simon 1972, Abelson 1973, Simon 1982, Anderson 1983, Kohonen 1984, Holland et
al 1986, Margolis 1987, Khong 1992, Reber 1993, Political Psychology 2003). Indeed, it is not far
off the mark to suggest the ultimate basis of all human epistemology is discrete pattern
identification. As Wolfram puts it, "observers will tend to be computationally equivalent to the
systems they observe," (Wolfram, 2002, 737) an observation we will expound upon shortly.

Hudson, Schrodt and Whitmer (2004) was an initial descriptive validation of the potential of this
approach. Since no one had looked for patterns in this fashion before, we first needed to
demonstrate that we could find them, and that the patterns had some plausible correspondence to
our underlying qualitative understanding of the situation we were analyzing. In that research, we
developed a web-based tool for exploring pattern-based rules; this can be found at

http://kennedyosx.byu.edu/

. That site includes data from the Kansas Event Data System

(KEDS) project, and provides a number of well-documented facilities for recoding the data,
specifying rules, and visualizing event data as discrete patterns rather than scaled aggregations. In
particular, the inputs titled “patterns” and “display” allow a researcher to have the capability to
perform discrete pattern transformations on the graphic output. One can also experiment with
possible rules, then display whether those patterns account for any of the behavior in the set.

In our initial probe of the approach, we specified some very simple rules and then ascertained how
well they accounted for the behavior in the Israel-Palestine dyad. These rules were chosen from a
combination of the general theoretical literature and a qualitative assessments of what some experts
in the field assert are the rules these actors do use (e.g. Bickerton and Klausner 1998, Gauss 1998,
Gerner 1994, Goldstein et al 2001, Tessler 1994).

Wolfram himself provides encouragement that the rules need not be many, and neither do they need
be complex. For example, he states, “Simple and definite underlying rules can produce behavior so
complex that it seems free of obvious rules” (Wolfram, 2002, 752) and then goes on to elaborate
that in his years of experience analyzing complex systems,

But when in general does complexity occur? [I]f the rules for a particular system are
sufficiently simple, then the system will only ever exhibit purely repetitive behavior. If the
rules are slightly more complicated, then nesting will also often appear. But to get
complexity in the overall behavior of a system one needs to go beyond some threshold in
the complexity of its underlying rules. The remarkable discovery that we have made,
however, is that this threshold is typically extremely low. [I]t ultimately takes only very
simple rules to produce behavior of great complexity. . . . Instead, once the threshold for
complex behavior has been reached, what one usually finds is that adding complexity to the