Mining textual sources of data can be used to design studies and test theories at temporal and spatial scales unheard of in the past. This opens up new opportunities for conflict studies and ethnographic research. We conducted a semi-automated network analysis of the 2003–2010 Sudan Tribune online news articles and modeled ethnic-group conflict in Sudan. We tested whether an ethnic group’s connections to the environment (livestock, biomes, and other resources) and other ethnic groups was associated with severe conflict and peace terms and whether ethnic-group richness at a given geospatial location was associated with severe conflict. Ethnic groups with more connections to livestock, environmental resources, and those ethnic groups with denser environmental–resource networks in their sphere of influence had more co-occurrences with severe conflict terms. Ethnic groups that had more connections to biomes in their sphere of influence were co-associated with peace terms. Locations that had high ethnic-group richness were associated with a higher frequency of severe conflict terms.
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Degree centrality measures were normalized by the maximum possible number of nodes they could be connected to (N−1).
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This work is supported in part by the Office of Naval Research (ONR), United States Navy (ONR MURI N000140811186). We Additional support was provided by the center for Computational Analysis of Social and Organizational Systems (CASOS). The views and conclusions contained in this document are those of the authors and should not be interpreted as representing the official policies, either expressed or implied, of the Office of Naval Research, or the U.S. government.
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Van Holt, T., Johnson, J.C., Brinkley, J.D. et al. Structure of ethnic violence in Sudan: a semi-automated network analysis of online news (2003–2010). Comput Math Organ Theory 18, 340–355 (2012). https://doi.org/10.1007/s10588-012-9124-z
- Content analysis
- Social networks
- Ethnic mapping