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On 9th October 2019 an armed nationalist murdered two bypassing citizens in a killing spree directed at a synagogue in Halle, Germany. Instantly, a broad diffusion of information unfolded on Twitter. Traffic for tweets mentioning Halle reached a peak as high as a hundred times to average value of the days before. In this study we examine this immense increase in communication and observe temporal diffusion patterns in crisis communication. We compare the traffic of tweets generated in this incident against Twitter traffic persisted during two other crisis events as well as a regular trending topic. A discussion of information diffusion based on network theoretic measures during crisis and terror events is presented. Results show that active user’s behavior changes with the onset of the incidents in all events in focus–while popular user’s metrics are consistent throughout the data sets. actively tweeting and repeatedly engaging users are detected only in two data sets.

In this work we investigate the engagement of Twitter accounts in the starting phase of reaction cascades, i.e., in the follow-up stream of an original tweet. In a first case study, we focus on a selection of very popular Twitter users from politics and society. We find a small but constantly active set of seemingly automated accounts in the onset of cascades that may contribute to the multiplication of content–especially for well-known populist politicians.