Social network analysis for use in change of venue cases
 
                         Rasco, Michelle Mae; PhD

                         BAYLOR UNIVERSITY, 1998
 
                         SOCIOLOGY, SOCIAL STRUCTURE AND DEVELOPMENT (0700); SOCIOLOGY, DEMOGRAPHY (0938); LAW (0398)
 

                         Network analysis studies interactions between individuals and how these interactions create a framework
                         that can be studied, allowing influence in a community to be traced. The research in this dissertation
                         demonstrates that network analysis can be used to assess the level of bias within a community, an
                         important issue in change of venue cases. Based on previous research, a number of predictions are
                         made about typical network size and causes for variation in network size. Once these parameters are in
                         place, a mathematical model of potential juror bias is constructed and applied to an actual case. The goal
                         of this application is to allow the defendant in a specific legal case to argue for a change of venue based
                         on the magnitude of influence of those directly impacted by the events. While the average network size
                         for a North American is 20 other adults, only network members who live within the county are relevant for
                         this study. Research reveals that up to 30% of network ties are to individuals outside the metropolitan
                         area, thus reducing the network size estimate to 14. The model was further refined, reducing network
                         size for employees due to the presence of coworkers in the network and adding to the network due to
                         individuals who live with directly affected individuals. When the mathematical model was applied to the
                         specific case in question, two categories of individuals had to be calculated in separate ways. Beginning
                         with 194 shareholders, the network size of shareholders who live alone, those who live with another
                         shareholder, and shareholders who live with other adults were calculated. This resulted in a total network
                         size of 4,710 for shareholders. The second category consisted of former employees. The total number
                         of former employees was 236, and the network size for those who lived alone, with another employee, or
                         with other adults were calculated. The total network size for employees was 5,022. When combined with
                         the network size for shareholders, 9,732 adults within the county may reasonably be assumed to be
                         biased through their interaction with former employees and shareholders.

 


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