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As data are becoming increasingly central to journalistic practice, a number of technology-driven approaches are emerging among data journalists. This article focuses on sensor journalism, which brings new practical and ethical concerns to journalism. By interviewing and working with data journalists and journalism scholars, we analyze the new technological and ethical challenges that sensors bring to journalism. The results contribute to the knowledge on how data journalists implicitly embed ethical values into their everyday work. Furthermore, they suggest that general ethical values are revisited and extended by the influence of sensors.
From shock to shift
(2023)
We present a multi-dimensional, multi-level, and multi-channel approach to data visualization for the purpose of constructive climate journalism. Data visualization has assumed a central role in environmental journalism and is often used in data stories to convey the dramatic consequences of climate change and other ecological crises. However, the emphasis on the catastrophic impacts of climate change tends to induce feelings of fear, anxiety, and apathy in readers. Climate mitigation, adaptation, and protection—all highly urgent in the face of the climate crisis—are at risk of being overlooked. These topics are more difficult to communicate as they are hard to convey on varying levels of locality, involve multiple interconnected sectors, and need to be mediated across various channels from the printed newspaper to social media platforms. So far, there has been little research on data visualization to enhance affective engagement with data about climate protection as part of solution-oriented reporting of climate change. With this research we characterize the unique challenges of constructive climate journalism for data visualization and share findings from a research and design study in collaboration with a national newspaper in Germany. Using the affordances and aesthetics of travel postcards, we present Klimakarten, a data journalism project on the progress of climate protection at multiple spatial scales (from national to local), across five key sectors (agriculture, buildings, energy, mobility, and waste), and for print and online use. The findings from quantitative and qualitative analysis of reader feedback confirm our overall approach and suggest implications for future work.
Journalism has become more data-driven and inherently visual in recent years. Photographs, illustrations, infographics, data visualizations, and general images help convey complex topics to a wide audience. The way that visual artifacts influence how readers form an opinion beyond the text is an important issue to research, but there are few works about this topic. In this context, we research the persuasive, emotional and memorable dimensions of data visualizations and illustrations in journalistic storytelling for long-form articles. We conducted a user study and compared the effects which data visualizations and illustrations have on changing attitude towards a presented topic. While visual representations are usually studied along one dimension, in this experimental study, we explore the effects on readers' attitudes along three: persuasion, emotion, and information retention. By comparing different versions of the same article, we observe how attitudes differ based on the visual stimuli present, and how they are perceived when combined. Results indicate that the narrative using only data visualization elicits a stronger emotional impact than illustration-only visual support, as well as a significant change in the initial attitude about the topic. Our findings contribute to a growing body of literature on how visual artifacts may be used to inform and influence public opinion and debate. We present ideas for future work to generalize the results beyond the domain studied, the water crisis.
This article investigates data journalism epistemology through Michel Foucault’s definition of power. The growing demand for data-savvy reporters with computational skills has been proven to shift the newsrooms’ culture in media companies across the globe. Previous research has documented journalists’ shift towards a data-centred epistemology and the increasingly important role of computation and data-driven practices in newsrooms. By focusing on inexperienced journalists as they mobilise data journalism for the first time, this research openly discusses its epistemology as a form of Foucauldian power: which epistemological tensions – individual or structural – emerge among newcomers when reporting extensively with data? The article presents the case of a newly formed data journalism team at taz, a German cooperative media company. It is based on qualitative data collected through action research, namely six in-depth interviews, auto-ethnographic notes and self-reflective inquiries. Data are framed through Foucault’s concepts of power and will to truth. Results show the discord between data journalism epistemology and its practical implementation. Despite prioritising democratic access to data, technologies and non-hierarchical forms of cooperation, data journalism remains largely dependent on traditional methods and culture.
Data Stories of Water
(2023)
We present a methodology for making sense of the communicative role of data visualizations in journalistic storytelling and share findings from surveying water-related data stories. Data stories are a genre of long-form journalism that integrate text, data visualization, and other visual expressions (e.g., photographs, illustrations, videos) for the purpose of data-driven storytelling. In the last decade, a considerable number of data stories about a wide range of topics have been published worldwide. Authors use a variety of techniques to make complex phenomena comprehensible and use visualizations as communicative devices that shape the understanding of a given topic. Despite the popularity of data stories, we, as scholars, still lack a methodological framework for assessing the communicative role of visualizations in data stories. To this extent, we draw from data journalism, visual culture, and multimodality studies to propose an interpretative framework in six stages. The process begins with the analysis of content blocks and framing elements and ends with the identification of dimensions, patterns, and relationships between textual and visual elements. The framework is put to the test by analyzing 17 data stories about water-related issues. Our observations from the survey illustrate how data visualizations can shape the framing of complex topics.