| 1. |
- Haghighatkhah, Pantea, et al.
(författare)
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Characterizing Uncertainty in the Visual Text Analysis Pipeline
- 2022
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Annan publikation (övrigt vetenskapligt/konstnärligt)abstract
- Current visual text analysis approaches rely on sophisticated processing pipelines. Each step of such a pipeline potentially amplifies any uncertainties from the previous step. To ensure the comprehensibil- ity and interoperability of the results, it is of paramount importance to clearly communicate the uncertainty not only of the output but also within the pipeline. In this paper, we characterize the sources of uncertainty along the visual text analysis pipeline. Within its three phases of labeling, modeling, and analysis, we identify six sources, discuss the type of uncertainty they create, and how they propagate. The goal of this paper is to bring the attention of the visualization community to additional types and sources of uncer- tainty in visual text analysis and to call for careful consideration, highlighting opportunities for future research.
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| 2. |
- Haghighatkhah, Pantea, et al.
(författare)
-
Characterizing Uncertainty in the Visual Text Analysis Pipeline
- 2022
-
Ingår i: Proceedings - 2022 IEEE 7th Workshop on Visualization for the Digital Humanities, VIS4DH 2022. - 9781665476683 ; , s. 25-30
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Konferensbidrag (refereegranskat)abstract
- Current visual text analysis approaches rely on sophisticated processing pipelines. Each step of such a pipeline potentially amplifies any uncertainties from the previous step. To ensure the comprehensibility and interoperability of the results, it is of paramount importance to clearly communicate the uncertainty not only of the output but also within the pipeline. In this paper, we characterize the sources of uncertainty along the visual text analysis pipeline. Within its three phases of labeling, modeling, and analysis, we identify six sources, discuss the type of uncertainty they create, and how they propagate. The goal of this paper is to bring the attention of the visualization community to additional types and sources of uncertainty in visual text analysis and to call for careful consideration, highlighting opportunities for future research.
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| 3. |
- Kucher, Kostiantyn, Dr. 1989-, et al.
(författare)
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An Interdisciplinary Perspective on Evaluation and Experimental Design for Visual Text Analytics : Position Paper
- 2022
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Ingår i: Proceedings of the 2022 IEEE Workshop on Evaluation and Beyond — Methodological Approaches to Visualization (BELIV '22). - : IEEE. - 9798350396294 - 9798350396300 ; , s. 28-37
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Konferensbidrag (refereegranskat)abstract
- Appropriate evaluation and experimental design are fundamental for empirical sciences, particularly in data-driven fields. Due to the successes in computational modeling of languages, for instance, research outcomes are having an increasingly immediate impact on end users. As the gap in adoption by end users decreases, the need increases to ensure that tools and models developed by the research communities and practitioners are reliable, trustworthy, and supportive of the users in their goals. In this position paper, we focus on the issues of evaluating visual text analytics approaches. We take an interdisciplinary perspective from the visualization and natural language processing communities, as we argue that the design and validation of visual text analytics include concerns beyond computational or visual/interactive methods on their own. We identify four key groups of challenges for evaluating visual text analytics approaches (data ambiguity, experimental design, user trust, and "big picture" concerns) and provide suggestions for research opportunities from an interdisciplinary perspective.
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| 4. |
- Kucher, Kostiantyn, et al.
(författare)
-
An Interdisciplinary Perspective on Evaluation and Experimental Design for Visual Text Analytics : Position Paper
- 2022
-
Annan publikation (övrigt vetenskapligt/konstnärligt)abstract
- Appropriate evaluation and experimental design are fundamental for empirical sciences, particularly in data-driven fields. Due to the successes in computational modeling of languages, for instance, research outcomes are having an increasingly immediate impact on end users. As the gap in adoption by end users decreases, the need increases to ensure that tools and models developed by the research communities and practitioners are reliable, trustworthy, and supportive of the users in their goals. In this position paper, we focus on the issues of evaluating visual text analytics approaches. We take an interdisciplinary perspective from the visualization and natural language processing communities, as we argue that the design and validation of visual text analytics include concerns beyond com- putational or visual/interactive methods on their own. We identify four key groups of challenges for evaluating visual text analytics approaches (data ambiguity, experimental design, user trust, and “big picture” concerns) and provide suggestions for research oppor- tunities from an interdisciplinary perspective.
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| 5. |
- Rashik, Mashrur, et al.
(författare)
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Beyond Text and Speech in Conversational Agents: Mapping the Design Space of Avatars
- 2024
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Ingår i: Proceedings of the 2024 ACM Designing Interactive Systems Conference (DIS '24). - : Association for Computing Machinery (ACM). ; , s. 1875-1894
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Konferensbidrag (refereegranskat)abstract
- Conversational agents have gained widespread popularity due to their ability to simulate and sustain contextual conversations. Prior works predominantly focused on computational challenges. However, avatars — the representation of the agent — impact user interactions and perception of conversational agents’ trustworthiness and usefulness. Despite their importance, we lack a holistic understanding of conversational agent avatar design space. In this work, we address this gap by defining a categorization of 10 dimensions that is based on the analysis and iterative coding of 266 conversational agent papers from 160 venues spanning 2003 to the present. In addition, we built an interactive browser to facilitate exploration and interaction with these dimensions and their interrelationships. Our categorization lays the groundwork for researchers, designers, and practitioners to discern task-specific and contextual aspects of conversational agent avatar design. Our work fosters innovative ideas to facilitate new interactions with avatars by surfacing current patterns and highlighting open challenges.
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