TY - CHAP A1 - Kauer, Tobias A1 - Ridley, Arran A1 - Dörk, Marian A1 - Bach, Benjamin T1 - The Public Life of Data BT - Investigating Reactions to Visualizations on Reddit T2 - CHI Conference on Human Factors in Computing Systems (CHI ’21) N2 - This research investigates how people engage with data visualizations when commenting on the social platform Reddit. There has been considerable research on collaborative sensemaking with visualizations and the personal relation of people with data. Yet, little is known about how public audiences without specific expertise and shared incentives openly express their thoughts, feelings, and insights in response to data visualizations. Motivated by the extensive social exchange around visualizations in online communities, this research examines characteristics and motivations of people’s reactions to posts featuring visualizations. Following a Grounded Theory approach, we study 475 reactions from the /r/dataisbeautiful community, identify ten distinguishable reaction types, and consider their contribution to the discourse. A follow-up survey with 168 Reddit users clarified their intentions to react. Our results help understand the role of personal perspectives on data and inform future interfaces that integrate audience reactions into visualizations to foster a public discourse about data. KW - data visualization KW - reddit KW - personal data KW - Visualisierung KW - Personenbezogenen Daten Y1 - 2021 U6 - https://doi.org/10.1145/3411764.3445720 VL - 2021 SP - 1 EP - 12 PB - Association for Computing Machinery CY - New York ER - TY - JOUR A1 - Kauer, Tobias A1 - Akbaba, Derya A1 - Dörk, Marian A1 - Bach, Benjamin T1 - Discursive Patinas BT - Anchoring Discussions in Data Visualizations JF - IEEE transactions on visualization and computer graphics N2 - This paper presents discursive patinas, a technique to visualize discussions onto data visualizations, inspired by how people leave traces in the physical world. While data visualizations are widely discussed in online communities and social media, comments tend to be displayed separately from the visualization and we lack ways to relate these discussions back to the content of the visualization, e.g., to situate comments, explain visual patterns, or question assumptions. In our visualization annotation interface, users can designate areas within the visualization. Discursive patinas are made of overlaid visual marks (anchors), attached to textual comments with category labels, likes, and replies. By coloring and styling the anchors, a meta visualization emerges, showing what and where people comment and annotate the visualization. These patinas show regions of heavy discussions, recent commenting activity, and the distribution of questions, suggestions, or personal stories. We ran workshops with 90 students, domain experts, and visualization researchers to study how people use anchors to discuss visualizations and how patinas influence people's understanding of the discussion. Our results show that discursive patinas improve the ability to navigate discussions and guide people to comments that help understand, contextualize, or scrutinize the visualization. We discuss the potential of anchors and patinas to support discursive engagements, including critical readings of visualizations, design feedback, and feminist approaches to data visualization. KW - Annotation KW - Daten KW - Diskussion KW - Visualisierung Y1 - 2024 U6 - https://doi.org/10.1109/TVCG.2024.3456334 SN - 1077-2626 VL - 21 IS - 1 SP - 1246 EP - 1256 PB - Institute of Electrical and Electronics Engineers (IEEE) CY - New York ER - TY - JOUR A1 - Kauer, Tobias A1 - Dörk, Marian A1 - Bach, Benjamin T1 - Towards Collective Storytelling BT - Investigating Audience Annotations in Data Visualizations JF - IEEE Computer Graphics and Applications N2 - This work investigates personal perspectives in visualization annotations as devices for collective data-driven storytelling. Inspired by existing efforts in critical cartography, we show how people share personal memories in a visualization of COVID-19 data and how comments by other visualization readers influence the reading and understanding of visualizations. Analyzing interaction logs, reader surveys, visualization annotations, and interviews, we find that reader annotations help other viewers relate to other people's stories and reflect on their own experiences. Further, we found that annotations embedded directly into the visualization can serve as social traces guiding through a visualization and help readers contextualize their own stories. With that, they supersede the attention paid to data encodings and become the main focal point of the visualization. KW - Annotation KW - COVID-19 KW - Data Mining KW - Kartografie KW - Künstliche Intelligenz KW - Soziales Netzwerk KW - Visualisierung Y1 - 2025 U6 - https://doi.org/10.1109/MCG.2025.3547944 SN - 0272-1716 SN - 1558-1756 VL - 45 IS - 3 SP - 17 EP - 31 CY - New York ER -