Deborah J. Gerner

Validity Assessment of a Machine-Coded Event Data Set for the Middle East, 1982-92

This paper is a study of the validity of a machine-coded event data series for six Middle Eastern actors and the United States. The series is based on Reuters newswire story leads coded into the WEIS categories. The face validity of the data is assessed by examining the monthly net cooperation scores based on Goldsteins (1992) scale in comparison to narrative accounts of the interactions between the actors; the event data series clearly shows the major patterns of political interaction. The machinecoded data are also compared to a human-coded WEIS data set based on the The New York Times and Los Angeles Times. Almost all dyads show a statistically significant correlation between the number of events reported by the two series, as well as the number of cooperative events. About half of the dyads show significant correlation in net cooperation and the number of conflictual events; many of these differences appear to be due to the higher density of events in Reuters. Finally, the machine-coded and WEIS data sets are used in two statistical time series studies and are shown to produce generally comparable results. Validity Assessment... 2

MACHINE CODING OF EVENT DATA USING REGIONAL AND INTERNATIONAL SOURCES

This article discusses research on the machine coding of international event data from international and regional news sources using the Kansas Event Data System (KEDS). First, we suggest that the definition of an “event” should be modified so that events are explicitly and unambiguously defined in terms of natural language. Second, we discuss KEDS: a Macintosh-based machine coding system using pattern recognition and simple linguistic parsing to code events using the WEIS event categories. Third, we compare the Reuters international news service reports with those of two specialized regional sources: the foreign policy chronologies in the Journal of Palestine Studies and the German language biweekly publication Informationen . We conclude by noting that machine coding, when combined with the numerous sources of machine-readable text that have become available in the past decade, has the potential to provide a much richer source of event data on international political interactions than that currently available. The ease of machine coding should encourage the creation of event coding schemes developed to address specific theoretical concerns; the increased density of these new data sets may allow the study of problems that could not be analyzed before.

Reciprocity, Triangularity, and Cooperation in the Middle East, 1979-97

Does bilateral reciprocity or great-power influence (or both) promote the emergence of international cooperation in regional conflicts? Using machine-coded events data and vector autoregression, time-series analysis of 12 international dyads in the Middle East between 1979 and 1990 and 1991 and 1995 found bilateral reciprocity widespread in both time periods, characterizing nearly all dyads of sustained conflict and a majority of other dyads with various power and proximity characteristics. Significant triangular responses to U.S. actions occurred in only a few cases, although key ones—Iraq with its neighbors and Israel with Palestine. Neither bilateral reciprocity nor triangular response predicted changes in long-term conflict and cooperation. Rather, the presence of one or both of these response patterns appeared to be necessary, but not sufficient, conditions for regional states to increase long-term cooperation.

Cluster-Based Early Warning Indicators for Political Change in the Contemporary Levant

We use cluster analysis to develop a model of political change in the Levant as reflected in the World Event Interaction Survey coded event data generated from Reuters between 1979 and 1998. A new statistical algorithm that uses the correlation between dyadic behaviors at two times identifies clusters of political activity. The transition to a new cluster occurs when a point is closer in distance to subsequent points than to preceding ones. These clusters begin to “stretch” before breaking apart, which serves as an early warning indicator. The clusters correspond well with phases of political behavior identified a priori. A Monte Carlo analysis shows that the clustering and early warning measures are not random; they perform very differently in simulated data sets with similar statistical characteristics. Our study demonstrates that the statistical analysis of newswire reports can yield systematic early warning indicators, and it provides empirical support for the theoretical concept of distinct behavioral phases in political activity.

An Event Data Analysis of Third-Party Mediation in the Middle East and Balkans

Event data on the Israel-Lebanon and Israel-Palestinian conflicts in the Levant (1979-1999) and the Serbia-Croatia and Serbia-Bosnia conflicts in the Balkans (1991-1999) are used to test two sets of process-related hypotheses embedded in the theoretical and qualitative literatures on mediation. Cross-correlation analysis is used to examine the time delay in the effects of mediation on the level of violence over time. Results show that these effects vary somewhat, depending on the conflict, and differ substantially, depending on who is conducting the mediation. Whether conflict reduction is most effectively achieved with sanctions or rewards is tested. Results show that a reduction in violence is generally associated with mediation combined with conflictual action directed toward both of the antagonists and combined with cooperative action directed to the weaker antagonist.

Empirical Indicators of Crisis Phase in the Middle East, 1979-1995

A number of studies of crisis behavior assume that political behavior goes through a series of clear phases characterized by distinct patterns of interactions. Correct identification of these phases is important in crisis forecasting and in the application of mediation techniques such as preventive diplomacy. To date, empirical work with these data sets has identified crisis phases contextually (by human coders) rather than through any systematic procedures. This study uses several statistical techniques to identify and analyze phases in an event data set measuring the political behavior between eight Middle Eastern actors for the period July 1979 to June 1995, and concludes with observations on how these analytic approaches might be applied to the problem of crisis early warning.

Taking Your Academic Expertise Public: Lessons Learned Responding to the 11 September Crisis

The advantage of academic life is that society allows us to spend years reading things no one else reads, writing articles and books almost no one else reads, and traveling to places no one else travels to. But in times of crisis, when the totally unexpected becomes reality, society understandably expects that we serve our communities with knowledge, explanation, insights, and policy alternatives. The days, weeks, and months following the attacks of 11 September were such an occasion and many academics experienced sudden demands for public commentary and analysis. As international studies scholars, we have insights and knowledge that our communities require and desire, most notably in times of crisis. By responding to the best of our abilities, we are able to return something to society and help people understand more clearly the world in which we live. In this essay, we discuss how we handled this challenge in the wake of 11 September and the lessons we have learned through that process.