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    Topic Tomographies (TopTom): a Visual Approach to Distill Information From Media Streams

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    Date
    2019
    Author
    Gobbo, Beatrice ORCID
    Balsamo, Duilio ORCID
    Mauri, Michele ORCID
    Bajardi, Paolo ORCID
    Panisson, André ORCID
    CIUCCARELLI, PAOLO ORCID
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    Abstract
    In this paper we present TopTom, a digital platform whose goal is to provide analytical and visual solutions for the exploration of a dynamic corpus of user-generated messages and media articles, with the aim of i) distilling the information from thousands of documents in a low-dimensional space of explainable topics, ii) cluster them in a hierarchical fashion while allowing to drill down to details and stories as constituents of the topics, iii) spotting trends and anomalies. TopTom implements a batch processing pipeline able to run both in near-real time with time stamped data from streaming sources and on historical data with a temporal dimension in a cold start mode. The resulting output unfolds along three main axes: time, volume and semantic similarity (i.e. topic hierarchical aggregation). To allow the browsing of data in a multiscale fashion and the identification of anomalous behaviors, three visual metaphors were adopted from biological and medical fields to design visualizations, i.e. the flowing of particles in a coherent stream, tomographic cross sectioning and contrast-like analysis of biological tissues. The platform interface is composed by three main visualizations with coherent and smooth navigation interactions: calendar view, flow view, and temporal cut view. The integration of these three visual models with the multiscale analytic pipeline proposes a novel system for the identification and exploration of topics from unstructured texts. We evaluated the system using a collection of documents about the emerging opioid epidemics in the United States.
    BibTeX
    @article {10.1111:cgf.13714,
    journal = {Computer Graphics Forum},
    title = {{Topic Tomographies (TopTom): a Visual Approach to Distill Information From Media Streams}},
    author = {Gobbo, Beatrice and Balsamo, Duilio and Mauri, Michele and Bajardi, Paolo and Panisson, André and CIUCCARELLI, PAOLO},
    year = {2019},
    publisher = {The Eurographics Association and John Wiley & Sons Ltd.},
    ISSN = {1467-8659},
    DOI = {10.1111/cgf.13714}
    }
    URI
    https://doi.org/10.1111/cgf.13714
    https://diglib.eg.org:443/handle/10.1111/cgf13714
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    • 38-Issue 3

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    Eurographics Association copyright © 2013 - 2023 
    Send Feedback | Contact - Imprint | Data Privacy Policy | Disable Google Analytics
    Theme by @mire NV
    System hosted at  Graz University of Technology.
    TUGFhA