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A Survey on Visual Analytics for the Spatio-Temporal Exploration of Microblogging Content

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Abstract

User-generated content is a valuable source of information whose production increases year after year. Twitter data is a form of user-generated content that is frequently adopted to comment on life activities in several contexts. Thus, scientific interest in that data has increased in recent years. This paper focusses on visual analytics approaches addressing the microblogging content exchanged through Twitter. In particular, we concentrate our interest on approaches that consider spatial and temporal aspects and provide visual support. Articles from the major conferences, journals, and digital libraries have been collected, organized and compared based on different criteria such as research questions, application focus, analytical and visual methods adopted, and interaction provided. In addition to these comparisons, opportunities and challenges are illustrated to inspire future research.

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Notes

  1. According to (Pear Analytics, 2009), approximately 40% of the tweets belong to the category "Pointless babble", that is, people tweeting about for example having a nap or eating a cake.

  2. The complete list of surveyed papers can be found at https://drive.google.com/file/d/0B3jU2lRnhLhdNjlBcFJfQVZSOVE/view?usp=sharing

  3. For our purposes and for simplicity, the tables we present throughout the paper contain only a small subset of the surveyed papers and are limited to a single page. However, the tables containing all of the considered papers can be found as supplementary material.

  4. Terms such as “not specified NLP” or “generic classification” indicate that in some cases, the authors generically mention the use of for example NLP or classification with no further detail.

  5. Because the selection of a visual item in a single view is usually propagated to the other views (linking), this feature will not be further mentioned, but rather assumed as implicitly supported each time this type of interaction is cited.

  6. Although following the suggestions of a user study mentioned in the papers, the word cloud was removed, the new functionalities of Senseplace2 again appear to include this visualization (see the video at www.geovista.psu.edu/Senseplace2).

  7. https://public.tableau.com/profile/alex1172#!/vizhome/ResearchCategoryandapplicationfield2016/Sheet1

  8. https://public.tableau.com/profile/alex1172#!/vizhome/Analyticalmethodsanduserinvolvement2016/Sheet1

  9. https://public.tableau.com/profile/alex1172#!/vizhome/Visualmethodsandspatio-temporalaspects2016/Sheet1

  10. https://public.tableau.com/profile/alex1172#!/vizhome/Visualmethodscontent2016/Sheet1

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  1. Institute of Cartography, Dresden University of Technology, Dresden, Germany

    Alessio Bertone & Dirk Burghardt

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  1. Alessio Bertone
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Bertone, A., Burghardt, D. A Survey on Visual Analytics for the Spatio-Temporal Exploration of Microblogging Content. J geovis spat anal 1, 2 (2017). https://doi.org/10.1007/s41651-017-0002-6

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