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  • Picturing the Politics of Resistance: Using Image Metadata and Historical Network Analysis to Map the East German Opposition Movement, 1975–1990

    Melanie Conroy, Kimmo Elo

    Chapter from the book: Fridlund, M et al. 2020. Digital Histories: Emergent Approaches within the New Digital History.

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    This chapter uses network analysis to explore, visualise and analyse quantitative historical data related to political resistance movements in the former East Germany. The study applies historical network analysis (HNA) rooted in social network analysis (SNA) to shed light on the structure and dynamics of the geospatial social networks of a sample group within the East German opposition movement between 1975 and 1990. In particular the opportunities and limits of using network analysis for historical studies are discussed which demonstrates how network graphs can be useful for historical analysis. The network analysis is used to help the researcher to identify which individuals are more likely to be well integrated into the group and which individuals are less central to the group, regardless of which individuals are most well-known or prominent. In particular, we point to the fact that knowledge of the government’s repressive actions and the opposition movement’s attempts to evade repression are fundamental to understanding the geospatial and social changes within this group during this period.

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    Conroy M. & Elo K. 2020. Picturing the Politics of Resistance: Using Image Metadata and Historical Network Analysis to Map the East German Opposition Movement, 1975–1990. In: Fridlund, M et al (eds.), Digital Histories. Helsinki: Helsinki University Press. DOI: https://doi.org/10.33134/HUP-5-13
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    This is an Open Access chapter distributed under the terms of the Creative Commons Attribution 4.0 license (unless stated otherwise), which permits unrestricted use, distribution and reproduction in any medium, provided the original work is properly cited. Copyright is retained by the author(s).

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    Additional Information

    Published on Dec. 7, 2020

    DOI
    https://doi.org/10.33134/HUP-5-13


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