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Replication data for: An Event Data Set for the Arabian/Persian Gulf Region 1979-1997

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https://dataverse.harvard.edu/citation?persistentId=doi:10.7910/DVN/YXQZWY
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This study discusses a WEIS-coded event data set covering the Arabian/Persian Gulf region (Iran, Iraq, Kuwait, Oman, Saudi Arabia, Yemen, and the smaller Gulf states) for the period 15 April 1979 to 10 June 1997. The coded events cover international interactions among these states, as well as interactions with any other states or major international organizations. The data set is generated from Reuters news reports downloaded from the NEXIS data service and coded using the Kansas Event Data System (KEDS) machine-coding program. <br /><br /> The study begins with a review of the process of generating a machine-coded data set, including a discussion of software we have developed to partially automate the development of dictionaries to code new geographical regions. The Gulf data are coded using a standard set of verb phrases (rather than phrases specifically adapted to the Gulf) and an actors dictionary that has been augmented only with the actors identified by a utility program that examines the source texts for acto rs not already found in the KEDS dictionary. <br /><br /> The Reuters reports generate 264,421 events when full stories are coded and 48,721 events when only lead sentences are coded. An examination of the time series that are generated when the events are aggregated by month using the Goldstein scale shows that they capture the major features of the behavior that we know to have occurred in the region. There is generally a high correlation (r > 0.75) between the series generated from lead-se ntences and from full stories when the major actors of the region (Iran, Iraq, Saudi Arabia and USA) are studied. An exception to this pattern is found in interactions involving a relatively minor actor, the United Arab Emirates. Here the full-story coding provides far more events than the lead-sentence coding and shows greater variance even for interactions between major actors. We expect this will also be the case for other small Gulf states, suggesting that full-story coding may be necessary for a complete analysis of these actors. <br /><br /> This study was presented at the annual meetings of the International Studies Association, Minneapolis, 18 - 22 March 1998.<br /><br /> <b>Gulf data set:</b> This data set covers the states of the Gulf region and the Arabian peninsula for the period 15 April 79 to 31 March 99. Texts after 10 June 97 were downloaded from the Reuters Business Briefing service; the countries involved were the same as in the NEXIS search. There are two versions of the data a set coded from the lead sentences only (57,000 events) a set coded from full stories (304,000 events) There is a high correlation (r > 0.75) between the two versions for major actor interactions aggregated with the Goldstein scale, but the full-story version is better for minor actors. The dictionaries used to code this data were updated to include all significant international actors identified by the Actor_Filter program. However, only a standard dictionary of verb phrases, not customized for the Gu lf, was used.
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Harvard Dataverse
创建时间:
2019-02-13
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