000 Informatik, Wissen, Systeme
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- 2023 (18) (entfernen)
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- Visualisierung (4)
- Journalismus (3)
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- Angststörung (2)
- Anxiety Disorder (1)
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The five editions of the CheckThat! lab so far have focused on the main tasks of the information verification pipeline: check-worthiness, evidence retrieval and pairing, and verification. The 2023 edition of the lab zooms into some of the problems and - for the first time - it offers five tasks in seven languages (Arabic, Dutch, English, German, Italian, Spanish, and Turkish): Task 1 asks to determine whether an item, text or a text plus an image, is check-worthy; Task 2 requires to assess whether a text snippet is subjective or not; Task 3 looks for estimating the political bias of a document or a news outlet; Task 4 requires to determine the level of factuality of a document or a news outlet; and Task 5 is about identifying authorities that should be trusted to verify a contended claim.
Unfolding Edges
(2023)
Existing work on visualizing multivariate graphs is primarily concerned with representing the attributes of nodes. Even though edges are the constitutive elements of networks, there have been only few attempts to visualize attributes of edges. In this work, we focus on the critical importance of edge attributes for interpreting network visualizations and building trust in the underlying data. We propose 'unfolding of edges' as an interactive approach to integrate multivariate edge attributes dynamically into existing node-link diagrams. Unfolding edges is an in-situ approach that gradually transforms basic links into detailed representations of the associated edge attributes. This approach extends focus+context, semantic zoom, and animated transitions for network visualizations to accommodate edge details on-demand without cluttering the overall graph layout. We explore the design space for the unfolding of edges, which covers aspects of making space for the unfolding, of actually representing the edge context, and of navigating between edges. To demonstrate the utility of our approach, we present two case studies in the context of historical network analysis and computational social science. For these, web-based prototypes were implemented based on which we conducted interviews with domain experts. The experts' feedback suggests that the proposed unfolding of edges is a useful tool for exploring rich edge information of multivariate graphs.
Tracing and Telling
(2023)
Cultural collections have transcended the boundaries of physical showcases and storage cabinets, evolving into intricate digital webs of interconnected data. The research project Restaging Fashion aimed to expand the possibilities for experiencing the linkages in digitized cultural heritage, focusing on the visualization of collection holdings related to the history of garments. Through graph-based narratives, the project investigated the complex interplay between the linear – and at times tentative – art historical discourses and the non-linear explorations of associated cultural heritage data. The resulting visualizations have been designed with the aim to allow for curated and dynamic exploration of the collection along research essays and their interrelated graphs.
Approximately four percent of the world’s population suffers from anxiety disorders. This makes anxiety disorders one of the most common mental illnesses and a significant global health concern. As social media is a primary source of health information and communication, this study aims at investigating how the hashtag #anxiety is used on Twitter and Instagram. The hashtag #anxiety was chosen because it is commonly used by the social media community to post or tweet about anxiety disorders, such as social anxiety, thus providing broad access to the data. We followed a quantitative approach and gathered open data from December 24th, 2019 to January 1st, 2020. Furthermore, we used a qualitative content analysis to detect topics and patterns within the data. Coding focused on identifying goals, motivations, and feelings concerning anxiety (disorders) and information sharing. Findings show that content and appearance of posts are strongly shaped by characteristics of the platforms. Additionally, the results unveil that both platforms serve as mediua for sharing information regarding mental health matters, such as personal experiences, challenges, and coping strategies, thereby cultivating a sense of community and support among users dealing with comparable issues. Twitter predominantly functions for real-time updates, in-situ interactions, and emergency communication, while Instagram's visual nature appears to offer a venue for creative expression through images and captions, illuminating the emotional and personal narratives of mental health journeys.
Social anxiety disorder (SAD) is one of the most commonly diagnosed anxiety disorders and a health concern that has a significant impact on the affected individuals’ quality of life. Although there is a need to develop methods and tools to support those affected by SAD, it is especially challenging to conduct participatory design with this psychologically vulnerable group of people. This paper presents the design, implementation and evaluation of a participatory format built on a toolkit, a cultural probe and an online prototyping workshop to gain insights into the challenges and needs experienced in the everyday lives of those affected by severe social anxiety. We provide the theoretical framework for designing a participatory format for this vulnerable group, introduce and discuss our methodological approach, and present the lessons learned from implementing and evaluating the format in two workshop sessions with a total of 15 participants.
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.
People Who Stare at Screens
(2023)
In November 2022, the US company OpenAI launched its chatbot ChatGPT built on top of its large language models (LLMs). “This chatbot has redefined the standards of artificial intelligence, proving that machines can indeed ‘learn’ the complexities of human language and interaction”, urteilte Forbes in May 2023.
As new trends constantly emerge worldwide, such as ChatGPT, it is necessary to approach the promotion of these tools to the broader population in an appropriate manner. New technologies and artificial intelligence tools simultaneously offer enhanced functionality but also the potential for misuse, such as plagiarism. Therefore, in the home countries of the authors, various discussions have been initiated at numerous universities and other organisations over the years regarding the advantages and disadvantages of these tools and how to best utilize them. It will be important for university teachers to actively integrate tools such as ChatGPT into their teaching and to critically reflect on the necessary competences for the use of such a chatbot. To achieve such learning objectives, the first step is to understand how ChatGPT works and how it can be used. In the following, the focus is on one such application, namely how ChatGPT can be used in cultural marketing.
Reflecting on the history and development of the knowledge management discipline from an academic and applied research perspective, this chapter will outline the KM essentials as core of the discipline and open questions to be addressed in the future. Secondly, the author will discuss in particular the role of KM within organizational practice in regard to the overall societal challenges all organizations are facing today globally. Thirdly, the chapter will provide an outlook of the discipline in the light of future developments and suggests some research topics to be addressed by interdisciplinary KM research in the future. Beside on drawing on more than 35 years of experience in the KM field, this contribution will profit from previous research undertaken on the future of KM (2002 and 2012), contributions to guidelines and standards for KM (e.g., CEN, DIN, ISO), as well as from working with European Fortune 500 companies over the past 25 years.