Thesis (Selection of subject)Thesis (Selection of subject)(version: 368)
Thesis details
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Political Violence in Turkey
Thesis title in Czech: Politické násilí v Turecku
Thesis title in English: Political Violence in Turkey
Key words: politické násilí, Turecko, terorismus, občanská válka
English key words: political violence, Turkey, terrorism, civil war
Academic year of topic announcement: 2020/2021
Thesis type: diploma thesis
Thesis language: angličtina
Department: Department of Security Studies (23-KBS)
Supervisor: doc. PhDr. Vít Střítecký, M.Phil., Ph.D.
Author: hidden - assigned by the advisor
Date of registration: 10.10.2020
Date of assignment: 07.07.2021
Date and time of defence: 23.09.2021 08:00
Venue of defence: Pekařská 16, JPEK312, 312, Malá učebna, 3.patro
Date of electronic submission:26.07.2021
Date of proceeded defence: 23.09.2021
Opponents: prof. PhDr. Emil Aslan, Ph.D.
 
 
 
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Preliminary scope of work
This thesis aims to create a novel dataset on political violence to estimate the accurate number of political violence incidents and fatalities in Turkey: Political Violence in Turkey Event Dataset (POLVITED). I argue that the reporting bias and differences in the scopes and definition of event datasets impact the quantitative study of conflict and violence. To eliminate the reporting bias and create a comprehensive dataset on political violence, I apply Matching EventData by Location, Time and Type (MELTT) method to the Global TerrorismDatabase(GTD) and Uppsala Conflict Data Programme (UCDP-GED). The finding suggests that UCDP-GED were able to record 65% of the total number of political violence incidents in Turkey, and GTD was able to record 45% of them while 10% is coded in both datasets. POLVITED enables the researchers to capture the accurate picture of political violence incidents in Turkey by eliminating the double recording and alleviating the reporting bias. Lastly, the comparison of POLVITED and official reports demonstrates that, although the reporting bias is inevitable, integration alleviates the problems associated with it by increasing the coverage of the dataset.
Preliminary scope of work in English
This thesis aims to create a novel dataset on political violence to estimate the accurate number of political violence incidents and fatalities in Turkey: Political Violence in Turkey Event Dataset (POLVITED). I argue that the reporting bias and differences in the scopes and definition of event datasets impact the quantitative study of conflict and violence. To eliminate the reporting bias and create a comprehensive dataset on political violence, I apply Matching EventData by Location, Time and Type (MELTT) method to the Global TerrorismDatabase(GTD) and Uppsala Conflict Data Programme (UCDP-GED). The finding suggests that UCDP-GED were able to record 65% of the total number of political violence incidents in Turkey, and GTD was able to record 45% of them while 10% is coded in both datasets. POLVITED enables the researchers to capture the accurate picture of political violence incidents in Turkey by eliminating the double recording and alleviating the reporting bias. Lastly, the comparison of POLVITED and official reports demonstrates that, although the reporting bias is inevitable, integration alleviates the problems associated with it by increasing the coverage of the dataset.
 
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