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Semantize: visualizing the sentiment of individual document

Published: 27 May 2014 Publication History

Abstract

A plethora of tools exist for extracting and visualizing key sentiment information from a corpus of text documents. Often, however, there is a need for quickly assessing the sentiment and feelings that arise from an individual document. We describe an interactive tool that visualizes the sentiment of a specific document such as an online opinion, blog, or transcript, by visually highlighting the sentiment features while leaving the document text intact.

References

[1]
Gregory, M. L., Chinchor, N., Whitney, P., Carter, R., Hetzler, E., & Turner, A. User-directed sentiment analysis: Visualizing the affective content of documents. Workshop on Sentiment and Subjectivity in Text. ACL (2006), 23--30.
[2]
Marcus, A., Bernstein, M. S., Badar, O., Karger, D. R., Madden, S., & Miller, R. C. Twitinfo: aggregating and visualizing microblogs for event exploration. In proceedings of CHI'11. ACM Press. (2011) 227--236.
[3]
Pang, B., & Lee L. Opinion mining and sentiment analysis. Foundations and trends in information retrieval 2.1-2 (2008) 1--135.
[4]
Zhang, J., Kawai, Y., Kumamoto, T., & Tanaka, K. A novel visualization method for distinction of web news sentiment. In Web Information Systems Engineering-WISE. Springer Berlin Heidelberg. (2009) 181--194.

Cited By

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  • (2024)An AI-Resilient Text Rendering Technique for Reading and Skimming DocumentsProceedings of the 2024 CHI Conference on Human Factors in Computing Systems10.1145/3613904.3642699(1-22)Online publication date: 11-May-2024
  • (2023)Scim: Intelligent Skimming Support for Scientific PapersProceedings of the 28th International Conference on Intelligent User Interfaces10.1145/3581641.3584034(476-490)Online publication date: 27-Mar-2023
  • (2023)Charagraph: Interactive Generation of Charts for Realtime Annotation of Data-Rich ParagraphsProceedings of the 2023 CHI Conference on Human Factors in Computing Systems10.1145/3544548.3581091(1-18)Online publication date: 19-Apr-2023
  • Show More Cited By

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  1. Semantize: visualizing the sentiment of individual document

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    Published In

    cover image ACM Other conferences
    AVI '14: Proceedings of the 2014 International Working Conference on Advanced Visual Interfaces
    May 2014
    438 pages
    ISBN:9781450327756
    DOI:10.1145/2598153
    Permission to make digital or hard copies of part or all 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 third-party components of this work must be honored. For all other uses, contact the Owner/Author.

    Sponsors

    • Centro Cultura Volta: Centro Cultura Volta
    • Politecnico di Milano: Politecnico di Milano

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    Association for Computing Machinery

    New York, NY, United States

    Publication History

    Published: 27 May 2014

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    Author Tags

    1. sentiment analysis
    2. user interface
    3. visualization

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    • Research-article

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    AVI' 14
    Sponsor:
    • Centro Cultura Volta
    • Politecnico di Milano

    Acceptance Rates

    AVI '14 Paper Acceptance Rate 32 of 112 submissions, 29%;
    Overall Acceptance Rate 128 of 490 submissions, 26%

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    Cited By

    View all
    • (2024)An AI-Resilient Text Rendering Technique for Reading and Skimming DocumentsProceedings of the 2024 CHI Conference on Human Factors in Computing Systems10.1145/3613904.3642699(1-22)Online publication date: 11-May-2024
    • (2023)Scim: Intelligent Skimming Support for Scientific PapersProceedings of the 28th International Conference on Intelligent User Interfaces10.1145/3581641.3584034(476-490)Online publication date: 27-Mar-2023
    • (2023)Charagraph: Interactive Generation of Charts for Realtime Annotation of Data-Rich ParagraphsProceedings of the 2023 CHI Conference on Human Factors in Computing Systems10.1145/3544548.3581091(1-18)Online publication date: 19-Apr-2023
    • (2022)Natural Language Processing and Cognitive Networks Identify UK Insurers’ Trends in Investor Day TranscriptsFuture Internet10.3390/fi1410029114:10(291)Online publication date: 12-Oct-2022
    • (2020)Affect-Aware Word CloudsACM Transactions on Interactive Intelligent Systems10.1145/337092810:4(1-25)Online publication date: 8-Nov-2020
    • (2019)Paralinguistic recommendations for affective word cloudsProceedings of the 24th International Conference on Intelligent User Interfaces10.1145/3301275.3302327(132-143)Online publication date: 17-Mar-2019
    • (2017)HiTextProceedings of the 26th International Conference on World Wide Web Companion10.1145/3041021.3054168(311-319)Online publication date: 3-Apr-2017
    • (2017)The State of the Art in Sentiment VisualizationComputer Graphics Forum10.1111/cgf.1321737:1(71-96)Online publication date: 12-Jun-2017

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