research-article

ConVisIT: Interactive Topic Modeling for Exploring Asynchronous Online Conversations

Authors:

Giuseppe CareniniAuthors Info & Claims

IUI '15: Proceedings of the 20th International Conference on Intelligent User Interfaces

Pages 169 - 180

https://doi.org/10.1145/2678025.2701370

Published: 18 March 2015 Publication History

Abstract

In the last decade, there has been an exponential growth of asynchronous online conversations thanks to the rise of social media. Analyzing and gaining insights from such conversations can be quite challenging for a user, especially when the discussion becomes very long. A promising solution to this problem is topic modeling, since it may help the user to quickly understand what was discussed in the long conversation and explore the comments of interest. However, the results of topic modeling can be noisy and may not match the user's current information needs. To address this problem, we propose a novel topic modeling system for asynchronous conversations that revises the model on the fly based on user's feedback. We then integrate this system with interactive visualization techniques to support the user in exploring long conversations, as well as revising the topic model when the current results are not adequate to fulfill her information needs. An evaluation with real users illustrates the potential benefits of our approach for exploring conversations, when compared to both a traditional interface as well as an interactive visual interface that does not support human-in-the-loop topic model.

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Cited By

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Steimann JBrenneis MMauve M(2024)Is This Comment More Relevant? Understanding the Structural Aspects of Relevance in Comment SectionsHuman Interface and the Management of Information10.1007/978-3-031-60107-1_19(264-278)Online publication date: 1-Jun-2024
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Index Terms

ConVisIT: Interactive Topic Modeling for Exploring Asynchronous Online Conversations
1. Computing methodologies
  1. Artificial intelligence
    1. Natural language processing
      1. Language resources
2. Human-centered computing
  1. Human computer interaction (HCI)

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cover image ACM Conferences

IUI '15: Proceedings of the 20th International Conference on Intelligent User Interfaces

March 2015

480 pages

ISBN:9781450333061

DOI:10.1145/2678025

General Chairs:
Oliver Brdiczka
Vectra Networks, Inc.
,
Polo Chau
Georgia Tech
,
Program Chairs:
Giuseppe Carenini
University of British Columbia
,
Shimei Pan
University of Maryland
,
Per Ola Kristensson
University of Cambridge

Copyright © 2015 ACM.

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Published: 18 March 2015

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Natural Sciences and Engineering Research Council of Canada

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IUI'15

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IUI'15: IUI'15 20th International Conference on Intelligent User Interfaces

March 29 - April 1, 2015

Georgia, Atlanta, USA

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IUI '15 Paper Acceptance Rate 47 of 205 submissions, 23%;

Overall Acceptance Rate 746 of 2,811 submissions, 27%

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IUI '25

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Cagliari , Italy

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https://dl.acm.org/doi/10.1145/3613904.3642667
Steimann JMauve M(2024)Developing Custom-Made Comment-Recommendation Prototypes with a Modular Design FrameworkSocial Computing and Social Media10.1007/978-3-031-61281-7_7(97-112)Online publication date: 1-Jun-2024
https://doi.org/10.1007/978-3-031-61281-7_7
Steimann JBrenneis MMauve M(2024)Is This Comment More Relevant? Understanding the Structural Aspects of Relevance in Comment SectionsHuman Interface and the Management of Information10.1007/978-3-031-60107-1_19(264-278)Online publication date: 1-Jun-2024
https://doi.org/10.1007/978-3-031-60107-1_19
Rehman KWakabayashi K(2023)Keyphrase-based Refinement Functions for Efficient Improvement on Document-Topic Association in Human-in-the-Loop Topic ModelsJournal of Information Processing10.2197/ipsjjip.31.35331(353-364)Online publication date: 2023
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Khan MWakabayashi K(2023)Reducing Human Effort in Keyphrase-Based Human-in-the-Loop Topic Models: A Method for Keyphrase RecommendationsInformation Integration and Web Intelligence10.1007/978-3-031-48316-5_24(233-248)Online publication date: 22-Nov-2023
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