Detecting unfolding crises with Visual Analytics and Conceptual Maps Emerging phenomena and big data

Detecting the emergence of a political crisis is a key goal of security informatics. Big data provides us with valuable information on the many socio-economic indicators of crisis dynamics, ranging from unemployment to the trustworthiness of political institutions. However, it is currently challenging to link information on these factors in order for analysts to assess the possible directions of a conflict. At present, while some solutions offer theoretical frameworks for understanding those indicators in the abstract, these frameworks cannot easily be operationalised to the level needed for automatic processing of big data streams. Alternative solutions do automatically code political events, but only offer a high level picture that cannot support the analysis of deeper conflict processes. In this paper, we combine Visual Analytics with Concept Maps to support analysts in monitoring conflicts. Visual Analytics allows the interactive visual exploration of data, while Concept Maps keep this exploration focused by linking data patterns (e.g., occurrence and frequency of keywords) to underlying dynamics (e.g., coordination of activism, salience of violence). We illustrate the potential of our approach through a discussion of how it could be used to study the on-going Syrian crisis. While this approach still requires validation with analysts, we fully specify the technical structure of our approach and exemplify its use to detect shifts in political stability.