University of Louisville
Social Behavior and Genocide Crimes in Rwanda: An Analysis of the Social Networks of Convicted Genocide Perpetrator, Hassan Ngeze
Institution
University of Louisville
Faculty Advisor/ Mentor
Jennie Burnet
Abstract
This project is a part of a larger ongoing study examining rescuer behavior and the roles of Muslims in the Rwandan genocide. The project aims to document and understand the social network connections of key actors in the genocide using data drawn from the International Criminal Tribunal for Rwanda online archives and other sources. We hypothesize that the social network characteristics of Hassan Ngeze will reveal factors common to high-level genocide perpetrators and suggest social network characteristics that should be explored for rescuers. For this project, social network data was mined from published sources; entered into a database that documents connections between individuals, groups, events, organizations, and geographic locations; the data was then imported into UCINET, a software package designed for analyzing the characteristics of whole social networks. Data analysis considered node characteristics, like degree centrality, betweenness centrality; closeness tie characteristics, such as strength; and network characteristics, such as structural cohesion and clustering. The social network data and analysis will be used to develop interview questions for the new data to be gathered.
Social Behavior and Genocide Crimes in Rwanda: An Analysis of the Social Networks of Convicted Genocide Perpetrator, Hassan Ngeze
This project is a part of a larger ongoing study examining rescuer behavior and the roles of Muslims in the Rwandan genocide. The project aims to document and understand the social network connections of key actors in the genocide using data drawn from the International Criminal Tribunal for Rwanda online archives and other sources. We hypothesize that the social network characteristics of Hassan Ngeze will reveal factors common to high-level genocide perpetrators and suggest social network characteristics that should be explored for rescuers. For this project, social network data was mined from published sources; entered into a database that documents connections between individuals, groups, events, organizations, and geographic locations; the data was then imported into UCINET, a software package designed for analyzing the characteristics of whole social networks. Data analysis considered node characteristics, like degree centrality, betweenness centrality; closeness tie characteristics, such as strength; and network characteristics, such as structural cohesion and clustering. The social network data and analysis will be used to develop interview questions for the new data to be gathered.