Automated Production of High-Volume, Real-Time Political Event Data
Philip A. Schrodt
Pennsylvania State University
APSA 2010 Annual Meeting Paper
This paper summarizes the current state-of-the-art for generating high-volume, near-real-time event data using automated coding methods, based on recent efforts for the DARPA Integrated Crisis Early Warning System (ICEWS) and NSF-funded research. The ICEWS work expanded by more than two orders of magnitude previous automated coding efforts, coding of about 26-million sentences generated from 8-million stories condensed from around 30 gigabytes of text. The actual coding took six minutes. The paper is largely a general "how-to" guide to the pragmatic challenges and solutions to various elements of the process of generating event data using automated techniques. It also discusses a number of ways that this could be augmented with existing open-source natural language processing software to generate a third-generation event data coding system.
Number of Pages in PDF File: 26
Keywords: event data, ICEWS, prediction, natural language processing, DARPA, open sourceworking papers series
Date posted: July 19, 2010 ; Last revised: August 31, 2010
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