From Words to Numbers to Graphs: A Suggestion on How to Analyze Inter-Organizational Networks Using Archival Sources

Type: 
Lecture
Audience: 
Open to the Public
Building: 
Nador u. 9, Monument Building
Room: 
Gellner Room
Monday, December 7, 2009 - 5:30pm
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Date: 
Monday, December 7, 2009 - 5:30pm to 7:00pm

In most studies on (inter-organizational) networks relational information is either gathered through questionnaires or extracted from lists or registers. However, there are instances in which these data collection procedures cannot be used either because variables, indicators and data cannot be aligned, because respondents are not available or because lists and registers do not exist. Moreover, organizations have been producing written records in abundance since the beginning of the 20th century. Therefore, a technique is proposed extending the work by Roberto Franzosi, which combines content analysis and network analysis to extract and analyze relational data from written texts such as letters, protocols, or more recently emails. It is suggested that this technique could become a valuable addition to the available data collection procedures in social network analysis to date. The technique is introduced and discussed by presenting results from a research project on the persecution of Jews in Western Europe under German occupation from 1940-1944.

Jorg Raab (PhD Konstanz, Germany, 2000) is assistant professor of Organization Studies at Tilburg University, NL. Raab conducts research on the effectiveness and management of inter-organizational networks, on the impact of inter-organizational networks on the Holocaust in France, Belgium and the Netherlands and on “Dark Networks” (terrorism, illegal arms trading, illegal drugs). Moreover, he participates in a research project on the recent institutional changes in the Dutch day care sector. In his work, Raab tries to understand how policy outcomes and public services come about through the joint efforts of actors in the public, non-profit, and private sectors. He analyses inter-organizational networks in different settings with quantitative and qualitative methods.