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A study on human-generated tag structures to inform tag cloud layout

Published: 27 May 2014 Publication History

Abstract

Tag clouds are popular features on web pages, not only to support browsing but also to provide an overview over the content of the page or to summarize search retrieval results. Commonly, the arrangement of tags is based on a random layout or an alphabetic ordering of the tags. Previous research suggests to further structure the tag clouds according to semantics, typically employing cooccurrence-based relations to assess the semantic relatedness of two tags. Regarding the layout of the resulting structure, a wide variety of representations has been proposed. However, only few papers motivate their design choice or evaluate its performance from the perspective of a user, leaving it open if the approach answers the users' expectations. In this paper we present the results of a study in which we observed how humans structure user-generated tags of a social bookmarking system given the task that the resulting layout should provide a quick overview over a search retrieval result. We examine the participants' layouts based on the final arrangement of tags and a detailed interview conducted after the task. Thereby, we analyze and characterize the different term relations employed as well as the higher-level structures generated. The deeper understanding of what criteria are considered important by humans can inform the design of automatic algorithms as well as future studies evaluating their performance.

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  • (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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    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 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 the author(s) 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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    • Centro Cultura Volta: Centro Cultura Volta
    • Politecnico di Milano: Politecnico di Milano

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    New York, NY, United States

    Publication History

    Published: 27 May 2014

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    Author Tags

    1. semantic
    2. structured
    3. tag clouds
    4. user study
    5. visualization

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    AVI' 14
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    • Centro Cultura Volta
    • Politecnico di Milano

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

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    • (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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