Our paper presents first analysis of Czech Twitter content within the agriculture context. We deployed textual analysis of more than 240,000 tweets over 2014-2019 hashtags that were, according to Google Trends, most trending and related to Czech agriculture such as #dotace, #repka, or #bionafta-both in Czech and English language. Besides descriptive statistics of the tweet dataset, we visualized keyword correlations which revealed strong focus of the discourse on rapeseed, biofuel and the prime minister Andrej Babiš. Owing to inherent political context of the given hashtags, we found spikes in topics which followed the public attention to the topics in mass media. We also found several accounts that produces high traffic for certain hashtags in Czech, yet those accounts were located abroad. Consistent with other studies, a high proportion of tweets was generated by unverified accounts that might be bots-automated accounts. We propose to conduct semantic analysis of a broader dataset over the main social media platforms in the Czech Republic.

Building capacity for carrying out and understanding responsible science that is relevant to local challenges is a key ingredient in the OPCW’s strategy for achieving and maintaining a world free of chemical weapons. Two important contexts for building that capacity for responsible science are (1) the global attention being drawn to the rapidly increasing human chemical footprint on our planet and (2) the pervasive use of digital technologies. We describe an effort coordinated by the Organisation for the Prohibition of Chemical Weapons to build capacity among young people around the world to harness the power of small mobile chemical sensors to develop data literacy in complex chemical analysis based on measuring analytes that are relevant to their lives and local contexts. This new type of data literacy is an emergent element in educational programs and is key to developing the capacity for decision-making on chemical measurement data. The project brings together student and faculty collaborators from the fields of chemistry, social sciences and informatics, to provide proof of concept in four areas that support the overall goal of building a collective effort for scientific analysis; the development of low cost environmental sensors for air and water samples; the collection of representative test data sets on priority contaminants; the assessment and visualization of data; and education about the effect of priority pollutants on human and environmental health. We report on the project goals and preliminary steps taken to achieve them.

We focus on trust development in dynamic, unstructured and non-commercial networked environments and conceptualize it as the process of producing a stable network ordering. We present a longitudinal, in-depth case study of the global humanitarian aid network, which is undergoing a disruptive transformation due to the emergence of digital volunteers who offer unique digital capacity for collecting and analyzing humanitarian aid data. Integrating this new actor-network into the existing global humanitarian network, comprised of formal organizations exhibits many problems that are concerned with trust. The ongoing inter-penetrating of these two networks is leading towards stabilizing into a new, qualitatively different network ordering that morphs the traditional and digital network models. We draw on sociology of translation, with its relational and performative sensibility, to analyze the network emerging and stabilizing as processes of trust development. We highlight the importance of four practices, performative of network trust: problematization, interessement, enrollment and mobilization.