This dissertation uses network visualization and analysis to explore how and why the nature of professional social networks of French artists (in particular painters) changed in the 19th century. It looks at the role of the Impressionists in this development through case studies, examines how this type of analysis can be used for art historical research in the form of a Virtual Research Environment (VRE), and concludes by discussing the future potential of VREs for the Digital Humanities in general.

The network visualization, created with data from the Union List of Artist Names (ULAN) and executed with Gephi, exemplifies how quantitative analysis can be used together with qualitative case studies as a way of “multi-scale reading” (Hochman and Manovich, 2013) to assist research in art history. The project finds that an increase in demand for innovation in French painting in the middle of the 19th century enabled innovative artists, some of whom later called themselves Impressionists, to break free from rigid structures and instigate a change from centralized to semi- and decentralized connections. Those artists played a crucial role in the formation of modernism, due as much to their revolutionary methods and techniques as to their dynamic, egalitarian social organization.

The creation of a VRE as unified environment based on a network visualization of artist’s connections has potential to become a future-oriented approach to art historical – and, more generally, Digital Humanities – research that is based on the use of new technologies to establish new research methods, rather than using new tools within the limits of existing methods.

Hochman, N. and Manovich, L., 2013. Zooming into an Instagram City: Reading the Local Through Social Media. First Monday, [online] 18(7). Available at: <http://firstmonday.org/ojs/index.php/fm/article/view/4711> [Accessed 28 Oct. 2018].

MA Digital Cultures Dissertation 2019 by Charlotte Krause

The full browser version of the visualization can be accessed here. Please make sure JavaScript is enabled in your browser to display the visualization.

The data set can be downloaded via Zenodo.