開始時刻
前のセッションの直後
139. Data-Driven Storytelling
発表数
6
時間
3分30秒
発表担当
目次
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Notable: On-the-fly Assistant for Data Storytelling in Computational Notebooks
説明
Computational notebooks are widely used for data analysis. Their interleaved displays of code and execution results (e.g., visualizations) are welcomed since they enable iterative analysis and preserve the exploration process. However, the communication of data findings remains challenging in computational notebooks. Users have to carefully identify useful findings from useless ones, document them with texts and visual embellishments, and then organize them in different tools. Such workflow greatly increases their workload, according to our interviews with practitioners. To address the challenge, we designed Notable to offer on-the-fly assistance for data storytelling in computational notebooks. It provides intelligent support to minimize the work of documenting and organizing data findings and diminishes the cost of switching between data exploration and storytelling. To evaluate Notable, we conducted a user study with 12 data workers. The feedback from user study participants verifies its effectiveness and usability.
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NetworkNarratives: Data Tours for Visual Network Exploration and Analysis
説明
This paper introduces semi-automatic data tours to aid the exploration of complex networks. Exploring networks requires significant effort and expertise and can be time-consuming and challenging. Distinct from guidance and recommender systems for visual analytics, we provide a set of goal-oriented tours for network overview, ego-network analysis, community exploration, and other tasks. Based on interviews with five network analysts, we developed a user interface (NetworkNarratives) and 10 example tours. The interface allows analysts to navigate an interactive slideshow featuring facts about the network using visualizations and textual annotations. On each slide, an analyst can freely explore the network and specify nodes, links, or subgraphs as seed elements for follow-up tours. Two studies, comprising eight expert and 14 novice analysts, show that data tours reduce exploration effort, support learning about network exploration, and can aid the dissemination of analysis results. NetworkNarratives is available online, together with detailed illustrations for each tour.
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Is It the End? Guidelines for Cinematic Endings in Data Videos
説明
Data videos are becoming increasingly popular in society and academia. Yet little is known about how to create endings that strengthen a lasting impression and persuasion. To fulfill the gap, this work aims to develop guidelines for data video endings by drawing inspiration from cinematic arts. To contextualize cinematic endings in data videos, 111 film endings and 105 data video endings are first analyzed to identify four common styles using the framework of ending punctuation marks. We conducted expert interviews (N=11) and formulated 20 guidelines for creating cinematic endings in data videos. To validate our guidelines, we conducted a user study where 24 participants were invited to design endings with and without our guidelines, which are evaluated by experts and the general public. The participants praise the clarity and usability of the guidelines, and results show that the endings with guidelines are perceived to be more understandable, impressive, and reflective.
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GeoCamera: Telling Stories in Geographic Visualizations with Camera Movements
説明
In geographic data videos, camera movements are frequently used and combined to present information from multiple perspectives. However, creating and editing camera movements requires significant time and professional skills. This work aims to lower the barrier of crafting diverse camera movements for geographic data videos. First, we analyze a corpus of 66 geographic data videos and derive a design space of camera movements with a dimension for geospatial targets and one for narrative purposes. Based on the design space, we propose a set of adaptive camera shots and further develop an interactive tool called GeoCamera. This interactive tool allows users to flexibly design camera movements for geographic visualizations. We verify the expressiveness of our tool through case studies and evaluate its usability with a user study. The participants find that the tool facilitates the design of camera movements.
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Communicating Consequences: Visual Narratives, Abstraction, and Polysemy in Rural Bangladesh
説明
Information communication and visualization practices reflect two centuries of developments of conventions and best practices which may not be reflective of global audiences’ methods for conveying information. Contrasting between rural traditional visual culture and contemporary HCI and data-visualization, we argue that an understanding of traditional practices for information visualization is required for building rich data-narratives and making data-driven systems more accessible and culturally situated. Our ten-month ethnographic study investigates how rural Bangladeshi communities construct narratives through visual media. \footnote{Caution: This paper contains visually disturbing images.} Our observation, interviews, and FGDs (n=54) expose how participants convey risk management, decision-making, and monetary management practices to their peers. We find that villagers used a rich network of polysemic symbols and abstractions to manifest subjectivity, factuality, consequence, situatedness, and uncertainty; varied visual attributes for constructing narratives; and emphasized material relations among components in visuals. These findings inform the design of future systems for decision support in a culturally situated manner.
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When do Data Visualizations Persuade? The Impact of Prior Attitudes on Learning about Correlations from Scatterplot Visualizations
説明
Data visualizations are vital to scientific communication on critical issues such as public health, climate change, and socioeconomic policy. They are often designed not just to inform, but to persuade people to make consequential decisions (e.g., to get vaccinated). Are such visualizations persuasive, especially when audiences have beliefs and attitudes that the data contradict? In this paper we examine the impact of existing attitudes (e.g., positive or negative attitudes toward COVID-19 vaccination) on changes in beliefs about statistical correlations when viewing scatterplot visualizations with different representations of statistical uncertainty. We find that strong prior attitudes are associated with smaller belief changes when presented with data that contradicts existing views, and that visual uncertainty representations may amplify this effect. Finally, even when participants' beliefs about correlations shifted their attitudes remained unchanged, highlighting the need for further research on whether data visualizations can drive longer-term changes in views and behavior.
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