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Very rich historical data allow us to tackle questions about dynamical historical processes that normally must be left aside by historians and other social scientists dealing with the phenomena of revolutionary change and mass mobilization. These data are reconstructed from more than 200 historical records and enlighten the behavior of about 5000 persons during the revolution and in the 15 years preceding it. The enormous historical information recovered from archived records by Prof. Dr. C. Lipp includes the participation of the city's inhabitants to more than 100 city-linked events such as participation in initiatives, membership in associations and constitution of the city's political institutions. This co-participation information allows to identify parts of the social structure and is available on the individual level . It can easily be combined with additional individual attributes such as occupation, land ownership, or confession. These extremely valuable data open the door to a new perspective on the study of social movements: a perspective that combines individualistic analysis with a structural view.
Still the question remains: how can one adequately deal with the immense amount of data that describe the social structure and the process of mobilization? Our methodological answer is one that combines statistical analysis with the use of visualization techniques of social structures. These techniques are based on force directed placement algorithms (Eades (1984), Kamada (1989) which can be extended to handle valued graphs and even two-mode data (Krempel, 1999, forthcoming). As we shall demonstrate these visualization techniques help to systematically reduce the information contained in the data while preserving the information about more specific phenomena.