1

Paper

Early Warning of Conflict in Southern Lebanon using Hidden Markov Models Schrodt, Philip A. Uploaded 08-24-1997 Keywords hidden Markov models event data early warning international crisis sequence analysis Middle East WEIS BCOW Abstract This paper extends earlier work on the application of hidden Markov models (HMMs) to the problem of forecasting international conflict. HMMs are a sequence comparison method widely used in computerized speech recognition as a computationally efficient method of generalizing a set of sequences observed in a noisy environment. The technique is easily be adapted to work with sequences of international event data. The paper provides a theoretical "micro-foundation" for the use of sequence comparison in conflict early- warning based on coadaptation of organizational standard operating procedures. The left-right (LR) HMM used in speech recognition is first extended to a left-right-left (LRL) model that allows a crisis to escalate and de-escalate. This model is tested for its ability to correctly discriminate between BCOW crisis that involve and do not involve war. The LRL model provides slightly more accurate classification than the LR model. The interpretation of the hidden states in the LRL models, however, is more ambiguous than in the LR model. The HMM is then applied to the problem of forecasting the outbreak of armed violence between Israel and Arab forces in south Lebanon during the period 1979 to 1997 (excluding 1982-1985). An HMM is estimated using six cases of "tit-for-tat" escalation, then fitted to the entire time period. The model identifies about half of the TFT conflictsÑincluding all of the training casesÑthat occur in the full sequence, with only one false positive. This result suggests that HMMs could be used in an event-based monitoring system. However, the fit of the model is very sensitive to the number of days in a sequence when no events occurred, and consequently the fit measure is ineffective as an early warning indicator. Nonetheless, in a subset of models, the maximum likelihood estimate of the sequence of hidden Markov states provides a robust early warning indicator with a three to six-month lead. These models are valid in a split-sample test, and the patterns of cross-correlation of the individual states of the model are consistent with the theoretical expectations. While this approach clearly needs further validation, it appears promising. The paper concludes with observations on the extent to which the HMM approach can be generalized to other categories of conflict, some suggestions on how the method of estimation can be improved, and the implications that sequence-based forecasting techniques have for theories of the causes of conflict.

2

Paper

Pattern Recognition of International Crises using Hidden Markov Models Schrodt, Philip A. Uploaded 06-30-1997 Keywords hidden Markov models event data early warning international crisis sequence analysis Middle East WEIS BCOW Abstract Event data are one of the most widely used indicators in quantitative international relations research. To date, most of the models using event data have constructed numerical indicators based on the characteristics of the events measured in isolation and then aggregated. An alternative approach is to use quantitative pattern recognition techniques to compare an existing sequence of behaviors to a set of similar historical cases. This has much in common with human reasoning by historical analogy while providing the advantages of systematic and replicable analysis possible using machine-coded event data and statistical models. This chapter uses "hidden Markov models" Ñ- a recently developed sequence- comparison technique widely used in computational speech recognition Ñ- to measure similarities among international crises. The models are first estimated using the Behavioral Correlates of War data set of historical crises, then applied to an event data set covering political behavior in the contemporary Middle East for the period April 1979 through February 1997. A split-sample test of the hidden Markov models perfectly differentiates crises involving war from those not involving war in the cases used to estimate the models. The models also provide a high level of discrimination in a set of test cases not used in the estimated, and most of the erroneously-classified cases have plausible distinguishing features. The difference between the war and nonwar models also correlates significantly with a scaled measure of conflict in the contemporary Middle East. This suggests that hidden Markov models could be used to develop conflict measures based on event similarities to historical conflicts rather than on aggregated event scores.

3

Paper

Conflict and Mediation Event Observations (CAMEO): A New Event Data Framework for the Analysis of Foreign Policy Interactions Schrodt, Philip A. Gerner, Deborah J. Abu-Jabr, Rajaa Yilmaz, Omur Uploaded 04-01-2002 Keywords event data mediation WEIS Middle East Balkans West Africa Abstract The Conflict and Mediation Events Observations (CAMEO) framework is a new event data coding scheme optimized for the study of third-party mediation in international disputes. We have developed and implemented this system using the TABARI automated coding program, and have generated data sets for the Balkans (1989-2002; N=69,620), Levant (1979-2002; N=146,283), and West Africa (1989-2002; N=17,468) from Reuters and Agence France Presse reports. We describe why we decided to develop a new coding system, rather than continuing to use the World Events Interaction Survey (WEIS) framework that we have used in earlier work. Our decision involved both known weaknesses in the WEIS system, and some additional problems that we have found occur when WEIS is coded using automated methods. We have addressed these problems in constructing CAMEO, as well as producing much more completed documentation than has been available for WEIS. In this paper, we make several statistical comparisons of CAMEO-coded and WEIS-coded data in the three geographical regions. When the data are aggregated to a general behavioral levelÑverbal cooperation, material cooperation, verbal conflict and material conflictÑmost of the data sets show a high correlation (r>0.90) in the number of WEIS and CAMEO events coded per month. However, as we expected, CAMEO consistently picks up a greater number of events involving material cooperation. CAMEO and WEIS show similar irregularities in the distribution of events by category. Finally, there is a very significant correlation (r>0.57) between the count of CAMEO events specifically dealing with mediation and negotiation, and a pattern-based measure of mediation we developed earlier from WEIS data. Appendices in the paper show the CAMEO coding framework and examples from the codebook.

4

Paper

Analyzing the Dynamics of International Mediation Processess in the Middle East and the former Yugoslavia Gerner, Deborah J. Schrodt, Philip A. Uploaded 06-28-2001 Keywords mediation event data cross-correlation conflict Middle East Abstract This paper discusses a new National Science Foundation-funded project that will examine the dynamics of third-party international mediation using statistical time-series analyses of political event data. Third-party mediation was attempted in over half of the conflicts in the post-WWII period and it is likely that the use of mediation has increased following the end of the Cold War. Surprisingly, there have been few systematic studies on mediation. Those that do exist have generally focused on relatively static contextual factors such as the the conflict's attributes and the prior relationship between the mediator and protagonists rather than on dynamic factors' both contextual and process that may contribute to the success or failure of mediation activities. In contrast, the extensive qualitative literature provides numerous hypotheses about dynamic aspects of mediation. This, however, primarily consists of case studies, often by mediation practitioners, that exhibit little cumulation and, when taken as a whole, are rife with contradictory assertions. The project will formally test a number of the hypotheses embedded in the theoretical and qualitative literatures on mediation, using automated coding of event data from news-wire sources and employing time-series and event- history methods. A system of specialized event codes that a sensitive to mediation activities will be developed, then events will be coded from news reports using the TABARI machine coding program. The research will look at the factors that influence (1) whether mediation is accepted by the parties in a conflict, (2) whether formal agreements are reached, and (3) whether the agreements actually reduce the level of conflict. The project will initially focus on conflicts in the Middle East, a region where the principal investigators have substantial field experience. After refining the statistical tests on the Middle East case, the analysis will be extended to event data on conflicts in the former Yugoslavia and West Africa. The paper presents the results of an empirical "plausibility probe" based on existing WEIS-coded event data for the Levant and the former Yugoslavia. It employs a simple measure of third-party mediation efforts as the independent variables and Goldstein-scaled cooperation as the dependent variable. In the Levant, we find a weak but consistent pattern of mediation correlating with past conflictual activity, and resulting in later increases in cooperation. In the former Yugoslavia, the analysis shows strikingly different results for the mediation efforts the UN, European states, and the US. All three respond to increased conflict, but the UN efforts correlate with greater conflict, the US efforts with greater cooperation, and the European efforts have no effect. These results are consistent with many of the qualitative assessments of these efforts, and suggest that the event data approach will produce credible results

5

Paper

Detecting United States Mediation Styles in the Middle East, 1979-1998 Schrodt, Philip A. Uploaded 03-04-1999 Keywords event data mediation Middle East time series hidden Markov models Abstract This research is part of the "Multiple Paths to Knowledge Project" sponsored by the James A. Baker III Institute for Public Policy, Rice University, and the Program in Foreign Policy Decision Making, Texas A&M University. The paper deals with the problem of determining whether the mediation styles used by four U.S. Secretaries of State -- George Schultz, James Baker, Warren Christopher and Madeline Albright -- are sufficiently distinct that they can be detected in event data. The mediation domain is the Israel-Palestinian conflict from April 1979 to December 1998, the event data are coded from the Reuters news service reports using the WEIS event coding scheme, and the classification technique is hidden Markov models. The models are estimated for each of the four Secretaries based on 16 randomly chosen 32-events sequences of USA>ISR and USA>PAL events during the term of the Secretary. Each month in the data set is then assigned to one of the four Secretarial styles based on the best-fitting model. The models differentiate the mediation styles quite distinctly and this method of detecting styles yields quite different results when applied to ISR-PAL data or random data. The "Baker" and "Albright" styles are most distinctive; the "Schultz" style is least; both results are consistent with many qualitative characterizations of these periods. A series of t-tests is then done on Goldstein-scaled scores to determine whether the mediation styles translate into statistically distinct interactions in the ISR>USA, ISR>PAL, PAL>USA and PAL>ISR dyads. While there are a number of statistically-significant differences when the full sample is used, these may be due simply to the overall changes Israel-Palestinian relations over the course of the time series. When tests are done on months that are out-of-term -- in other words, where the style of one Secretary is being employed during the term of another -- few statistically-significant differences are found, though there is someindication of a lag of a month or so between the change in style and the behavioral response. It appears that the effects of the differing styles are not captured by changes in aggregated data, possibly because these scales force behavior into a single conflict-cooperation dimension. Consistent with other papers in the "Multiple Paths to Knowledge" project, the paper contains commentary on how the research project was actually done, as well as the conventional presentation of results. The file includes the papers in Postscript and PDF formats, the event data (Levant, April 1979 to December 1998) used in the analysis, the C source code for estimating the hidden Markov models. This paper was presented at the International Studies Association meetings, Washington, 16-21 February 1999

6

Paper

An Event Data Set for the Arabian/Persian Gulf Region 1979-1997 Schrodt, Philip A. Gerner, Deborah J. Uploaded 04-12-1999 Keywords event data Middle East Persian Gulf automated coding Abstract This paper 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. The paper 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 actors not already found in the KEDS dictionary. 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-sentences 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. Paper was presented a year ago at the International Studies Association, Minneapolis, 18 - 22 March 1998 The file includes the papers in Postscript and PDF formats. The data set has been updated through March, 1999 and is available at the KEDS project web site, http://www.ukans.edu/~keds.

7

Paper

Using Cluster Analysis to Derive Early Warning Indicators for Political Change in the Middle East, 1979-1996 Schrodt, Philip A. Gerner, Deborah J. Uploaded 08-22-1996 Keywords event data conflict early warning Middle East cluster analysis genetic algorithms Abstract This paper uses event data to develop an early warning model of major political changes in the Levant for the period April 1979 to July 1996. Following a general review of statistical early warning research, the analysis focuses on the behavior of eight Middle Eastern actorsÑEgypt, Israel, Jordan, Lebanon, the Palestinians, Syria, the United States and USSR/RussiaÑusing WEIS-coded event data generated from Reuters news service lead sentences with the KEDS machine-coding system. The analysis extends earlier work (Schrodt and Gerner 1995) demonstrating that clusters of behavior identified by conventional statistical methods correspond well with changes in political behavior identified a priori. We employ a new clustering algorithm that uses the correlation between the dyadic behaviors at two points in time as a measure of distance, and identifies cluster breaks as those time points that are closer to later points than to preceding points. We also demonstrate that these data clusters begin to "stretch" prior to breaking apart; this characteristic is used as an early-warning indicator. A Monte- Carlo analysis shows that the clustering and early warning measures perform very differently in simulated data sets having the same mean, variance, and autocorrelation as the observed data (but no cross-correlation) which reduces the likelihood that the clustering patterns are due to chance. The initial analysis uses Goldstein's (1992) weighting system to aggregate the WEIS-coded data. In an attempt to improve on the Goldstein scale, we use a genetic algorithm to optimize the weighting of the WEIS event categories for the purpose of clustering. This does not prove very successful and only differentiates clusters in the first half of the data set, a result similar to one we obtained using the cross-sectional K- Means clustering procedure. Correlating the frequency of events in the twenty-two 2-digit WEIS categories, on the other hand, gives clustering and early warning results similar to those produced by the Goldstein scale. The paper concludes with some general remarks on the role of quantitative early warning and directions for further research. This paper was presented at the American Political Science Association, San Francisco, 28 August - 1 September 1996

8

Poster

Effects of Interviewer Gender and Hijab on Gender-Related Survey Responses: Findings from a Nationally-Representative Field Experiment in Morocco Benstead, Lindsay Uploaded 11-07-2010 Keywords Gender of Interviewer Effects Response Effects Interviewer Religious Dress Hijab Morocco Middle East Missing Data North Africa Women's Rights Muslim World Abstract Despite the recent expansion of surveying in the Muslim world, few published studies have addressed methodological questions, including how observable interviewer characteristics affect responses and data quality. Although there are a limited number of studies on interviewer dress effects, none examine interviewer gender. This study asks whether and why gender and religious dress affect responses to gender-related questions. Drawing upon original data from a nationally-representative, partially-randomized survey of 800 Moroccans conducted in 2007, the study finds strong evidence that gender and dress affect responses and item non-response. The paper argues that because hijab implies multiple personal, religious, and political dimensions of identity nested within gender identity, interviewer gender and dress must be considered as intersecting categories. For questions pertaining to women’s role in the public sphere, responses were affected by interviewer dress; respondents reported more progressive attitudes and were more likely to refuse to respond to female interviewers not wearing hijab than to veiled female interviewers and male interviewers. For support for gender equality in family law, results were affected by interviewer gender; respondents reported more liberal views and were more likely to fail to respond to female interviewers with both dress styles than male interviewers. Interviewer characteristics affected responses to more than half of the 174 questions included in the survey, including support for democracy and religiosity. Researchers conducting surveys should code and control for interviewer characteristics in order to reduce total survey error and better understand the social processes which generate public opinion in this crucial region.