The Kansas Event Data System: A Beginner's Guide with an Application to the Study of Media Fatigue in the Palestinian Intifada

This paper provides a general introduction to using KEDS, the Kansas Event Data System. KEDS is a Macintosh-based machine coding system for generating event data using pattern recognition and simple linguistic parsing. The system codes from machine-readable text describing international events; the NEXIS data service, optical character recognition and CD-ROM can provide such texts. The paper is targeted at researchers who are considering using KEDS to generate event data: it describes the overall process of generating and analyzing event data, as well as providing a FAQ (Frequently Asked Questions) section and an annotated bibliography of sources of information on event data. We illustrate the use of KEDS in political science research by examining the issue of "media fatigue": how does the number and type of events reported in public sources change as a conflict evolves? Using the first three years of the Palestinian intifada as a case study, we compare a machine-coded, Reuters-based event data set, a human-coded data set based on the New York Times and an independently-collected data set reporting levels of lethal violence during this period. As predicted by the media fatigue hypothesis, we find that the correlation between the three sources declines over time, and is generally proportional to the level of interest that the international media is showing to this region. The correlation between Reuters and the New York Times changes in a pattern that is similar to the correlation between these sources and the independent data source, suggesting that the correlation between the two news sources could be used as an indicator of the level of error in an event data set caused by media fatigue. Development of KEDS was funded by the National Science Foundation through Grants SES8910738, SBR-9410023 and SES90-25130 (Data Development in International Relations Project) and the University of Kansas General Research Fund Grant 3500-X0-0038. Brad Bennett, Doug Bond, Joe Bond, Shannon Davis, Ronald Francisco, Deborah Gerner, Phillip Huxtable, Tony Nownes, Jon Pevehouse, Julia Pitner, Uwe Reising, Scott Savaiano and Judy Weddle have served the difficult role of alphaand beta-testers of KEDS © 1996, Deborah J. Gerner and Philip A. Schrodt Gerner and Schrodt: KEDS Beginners Guide... Page 1