Moved by the tears of others: emotion networking in the heritage sphere

There is no heritage without emotional sharing and clashing. This article explores the involvement of divergent emotions in heritage making by discussing the debate series of Imagine IC and the Reinwardt Academy and zooming in on the commemoration of slavery and imagery of ‘Black Pete’ in the Netherlands. We introduce ‘emotion networking’ as a methodology to approach present-day heritage production, aiming for a novel approach to engage with ‘the collective’

Developing Data Stories in Digital Humanities: Challenges and Protocol

This article discusses the development of data-driven stories and the editorial processes underlying their production. Such ‘data stories’ have proliferated in journalism but are also increasingly developed within academia. Within CLARIAH, the Common Lab Infrastructure for the Arts and Humanities, we are developing data stories based on analyses of data and metadata available via the Media Suite, an online resource providing access to a wide range of multimedia collections. Although ‘data stories’ lack a clear definition, there are similarities between the processes that underlie journalistic and academic data stories. However, there are also differences, specifically when it comes to epistemological claims. In this article we discuss data stories as phenomenon and their use in journalism and in the Humanities, based on the three main elements of data stories: data, visualisation, and narration. This provides the context in which we developed an editorial protocol for the development of CLARIAH Media Suite Data Stories, which includes four phases: exploration, research, review, and publication. While exploration focuses on data selection, research focuses on narration. Visualisation plays a role in both of these phases. Review is geared towards quality control, and in the publication phase the data story is published and monitored. By discussing our editorial protocol, we hope to contribute to the debate about how to develop and account for academic data stories

Developing Data Stories as Enhanced Publications in Digital Humanities

This paper discusses the development of data-driven stories and the editorial processes underlying their production. Such ‘data stories’ have proliferated in journalism but are also increasingly developed within academia. Although ‘data stories’ lack a clear definition, there are similarities between the processes that underlie journalistic and academic data stories. However, there are also differences, specifically when it comes to epistemological claims. In this paper data stories as phenomenon and their use in journalism and in the Humanities form the context for the editorial protocol developed for CLARIAH Media Suite Data Stories

Data Stories in CLARIAH: Developing a Research Infrastructure for Storytelling with Heritage and Culture Data

Online stories, from blog posts to journalistic articles to scientific publications, are commonly illustrated with media (e.g. images, audio clips) or statistical summaries (e.g. tables and graphs). Such “illustrations” are the result of a process of acquiring, parsing, filtering, mining, representing, refining and interacting with data [3]. Unfortunately, such processes are typically taken for granted and seldom mentioned in the story itself. Although recently a wide variety of interactive data visualisation techniques have been developed (see e.g., [6]), in many cases the illustrations in such publications are static; this prevents different audiences from engaging with the data and analyses as they desire. In this paper, we share our experiences with the concept of “data stories” that tackles both issues, enhancing opportunities for outreach, reporting on scientific inquiry, and FAIR data representation [9]. In journalism data stories are becoming widely accepted as the output of a process that is in many aspects similar to that of a computational scholar: gaining insights by analyzing data sets using (semi-)automatized methods and presenting these insights using (interactive) visualizations and other textual outputs based on data [4] [7] [5] [6]. In the context of scientific output, data stories can be regarded as digital “publications enriched with or linking to related research results, such as research data, workflows, software, and possibly connections among them” [1]. However, as infrastructure for (peerreviewed) enhanced publications is in an early stage of development (see e.g., [2]), scholarly data stories are currently often produced as blog posts, discussing a relevant topic. These may be accompanied by illustrations not limited to a single graph or image but characterized by different forms of interactivity: readers can, for instance, change the perspective or zoom level of graphs, or cycle through images or audio clips. Having experimented successfully with various types and uses of data stories1 in the CLARIAH2 project, we are working towards a more generic, stable and sustainable infrastructure to create, publish, and archive data stories. This includes providing environments for reproduction of data stories and verification of data via “close reading”. From an infrastructure perspective, this involves the provisioning of services for persistent storage of data (e.g. triple stores), data registration and search (registries), data publication (SPARQL end-points, search-APIs), data visualization, and (versioned) query creation. These services can be used by environments to develop data stories, either or not facilitating additional data analysis steps. For data stories that make use of data analysis, for example via Jupyter Notebooks [8], the infrastructure also needs to take computational requirements (load balancing) and restrictions (security) into account. Also, when data sets are restricted for copyright or privacy reasons, authentication and authorization infrastructure (AAI) is required. The large and rich data sets in (European) heritage archives that are increasingly made interoperable using FAIR principles, are eminently qualified as fertile ground for data stories. We therefore hope to be able to present our experiences with data stories, share our strategy for a more generic solution and receive feedback on shared challenges

A global experiment on motivating social distancing during the COVID-19 pandemic

Finding communication strategies that effectively motivate social distancing continues to be a global public health priority during the COVID-19 pandemic. This cross-country, preregistered experiment (n = 25,718 from 89 countries) tested hypotheses concerning generalizable positive and negative outcomes of social distancing messages that promoted personal agency and reflective choices (i.e., an autonomy-supportive message) or were restrictive and shaming (i.e., a controlling message) compared with no message at all. Results partially supported experimental hypotheses in that the controlling message increased controlled motivation (a poorly internalized form of motivation relying on shame, guilt, and fear of social consequences) relative to no message. On the other hand, the autonomy-supportive message lowered feelings of defiance compared with the controlling message, but the controlling message did not differ from receiving no message at all. Unexpectedly, messages did not influence autonomous motivation (a highly internalized form of motivation relying on one’s core values) or behavioral intentions. Results supported hypothesized associations between people’s existing autonomous and controlled motivations and self-reported behavioral intentions to engage in social distancing. Controlled motivation was associated with more defiance and less long-term behavioral intention to engage in social distancing, whereas autonomous motivation was associated with less defiance and more short- and long-term intentions to social distance. Overall, this work highlights the potential harm of using shaming and pressuring language in public health communication, with implications for the current and future global health challenges

A multi-country test of brief reappraisal interventions on emotions during the COVID-19 pandemic.

The COVID-19 pandemic has increased negative emotions and decreased positive emotions globally. Left unchecked, these emotional changes might have a wide array of adverse impacts. To reduce negative emotions and increase positive emotions, we tested the effectiveness of reappraisal, an emotion-regulation strategy that modifies how one thinks about a situation. Participants from 87 countries and regions (n = 21,644) were randomly assigned to one of two brief reappraisal interventions (reconstrual or repurposing) or one of two control conditions (active or passive). Results revealed that both reappraisal interventions (vesus both control conditions) consistently reduced negative emotions and increased positive emotions across different measures. Reconstrual and repurposing interventions had similar effects. Importantly, planned exploratory analyses indicated that reappraisal interventions did not reduce intentions to practice preventive health behaviours. The findings demonstrate the viability of creating scalable, low-cost interventions for use around the world

Sensory ecologies:the refinement of movement and the senses in sport

Global Challenges (FSW