research-article

The semantics of clustering: analysis of user-generated spatializations of text documents

Authors:

Scotland Leman,

Chris NorthAuthors Info & Claims

AVI '12: Proceedings of the International Working Conference on Advanced Visual Interfaces

Pages 555 - 562

https://doi.org/10.1145/2254556.2254660

Published: 21 May 2012 Publication History

Abstract

Analyzing complex textual datasets consists of identifying connections and relationships within the data based on users' intuition and domain expertise. In a spatial workspace, users can do so implicitly by spatially arranging documents into clusters to convey similarity or relationships. Algorithms exist that spatialize and cluster such information mathematically based on similarity metrics. However, analysts often find inconsistencies in these generated clusters based on their expertise. Therefore, to support sensemaking, layouts must be co-created by the user and the model. In this paper, we present the results of a study observing individual users performing a sensemaking task in a spatial workspace. We examine the users' interactions during their analytic process, and also the clusters the users manually created. We found that specific interactions can act as valuable indicators of important structure within a dataset. Further, we analyze and characterize the structure of the user-generated clusters to identify useful metrics to guide future algorithms. Through a deeper understanding of how users spatially cluster information, we can inform the design of interactive algorithms to generate more meaningful spatializations for text analysis tasks, to better respond to user interactions during the analytics process, and ultimately to allow analysts to more rapidly gain insight.

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Jiang SShen JWu SCai YYu YZhou Y(2023)Towards Usable Neural Comment Generation via Code-Comment Linkage Interpretation: Method and Empirical StudyIEEE Transactions on Software Engineering10.1109/TSE.2022.321485949:4(2239-2254)Online publication date: 1-Apr-2023
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Yang YDwyer TWybrow MLee BCordeil MBillinghurst MThomas B(2022)Towards Immersive Collaborative SensemakingProceedings of the ACM on Human-Computer Interaction10.1145/35677416:ISS(722-746)Online publication date: 14-Nov-2022
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Index Terms

The semantics of clustering: analysis of user-generated spatializations of text documents
1. Human-centered computing

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Published In

cover image ACM Other conferences

AVI '12: Proceedings of the International Working Conference on Advanced Visual Interfaces

May 2012

846 pages

ISBN:9781450312875

DOI:10.1145/2254556

Editors:
Genny Tortora
Università di Salerno, Italy
,
Stefano Levialdi
Sapienza Università di Roma, Italy
,
Maurizio Tucci
Università di Salerno, Italy

Copyright © 2012 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Consulta Umbria SRL
University of Salerno: University of Salerno

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 21 May 2012

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Division of Computing and Communication Foundations

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AVI'12

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University of Salerno

AVI'12: International Working Conference on Advanced Visual Interfaces

May 21 - 25, 2012

Capri Island, Italy

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Overall Acceptance Rate 128 of 490 submissions, 26%

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Cited By

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https://dl.acm.org/doi/10.1145/3643834.3660729
Jiang SShen JWu SCai YYu YZhou Y(2023)Towards Usable Neural Comment Generation via Code-Comment Linkage Interpretation: Method and Empirical StudyIEEE Transactions on Software Engineering10.1109/TSE.2022.321485949:4(2239-2254)Online publication date: 1-Apr-2023
https://doi.org/10.1109/TSE.2022.3214859
Yang YDwyer TWybrow MLee BCordeil MBillinghurst MThomas B(2022)Towards Immersive Collaborative SensemakingProceedings of the ACM on Human-Computer Interaction10.1145/35677416:ISS(722-746)Online publication date: 14-Nov-2022
https://dl.acm.org/doi/10.1145/3567741
Tahmid ILisle LDavidson KNorth CBowman D(2022)Evaluating the Benefits of Explicit and Semi-Automated Clusters for Immersive Sensemaking2022 IEEE International Symposium on Mixed and Augmented Reality (ISMAR)10.1109/ISMAR55827.2022.00064(479-488)Online publication date: Oct-2022
https://doi.org/10.1109/ISMAR55827.2022.00064
Tanhaei GTroost IHardman LHurst W(2022)Designing a Topic-Based Literature Exploration Tool in AR - An exploratory study for neuroscience2022 IEEE International Symposium on Mixed and Augmented Reality Adjunct (ISMAR-Adjunct)10.1109/ISMAR-Adjunct57072.2022.00099(471-476)Online publication date: Oct-2022
https://doi.org/10.1109/ISMAR-Adjunct57072.2022.00099
Bian YNorth CKrokos EJoseph S(2021)Semantic Explanation of Interactive Dimensionality Reduction2021 IEEE Visualization Conference (VIS)10.1109/VIS49827.2021.9623322(26-30)Online publication date: Oct-2021
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Norambuena BMitra TNorth C(2021)Narrative Sensemaking: Strategies for Narrative Maps Construction2021 IEEE Visualization Conference (VIS)10.1109/VIS49827.2021.9623296(181-185)Online publication date: Oct-2021
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Cui ZKancherla JBravo HElmqvist N(2019)Sherpa: Leveraging User Attention for Computational Steering in Visual Analytics2019 IEEE Visualization in Data Science (VDS)10.1109/VDS48975.2019.8973384(48-57)Online publication date: Oct-2019
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Liu SWang XCollins CDou WOuyang FEl-Assady MJiang LKeim D(2019)Bridging Text Visualization and Mining: A Task-Driven SurveyIEEE Transactions on Visualization and Computer Graphics10.1109/TVCG.2018.283434125:7(2482-2504)Online publication date: 1-Jul-2019
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