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#London2012: Towards Citizen-Contributed Urban Planning Through Sentiment Analysis of Twitter Data

Author

Listed:
  • Anna Kovacs-Gyori

    (Department of Geoinformatics—Z_GIS, University of Salzburg, Austria)

  • Alina Ristea

    (Department of Geoinformatics—Z_GIS, University of Salzburg, Austria)

  • Clemens Havas

    (Department of Geoinformatics—Z_GIS, University of Salzburg, Austria)

  • Bernd Resch

    (Department of Geoinformatics—Z_GIS, University of Salzburg, Austria / Center for Geographic Analysis, Harvard University, USA)

  • Pablo Cabrera-Barona

    (Institute of Higher National Studies—IAEN, Ecuador / Latin American Social Sciences Institute—FLACSO, Ecuador)

Abstract

The dynamic nature of cities, understood as complex systems with a variety of concurring factors, poses significant challenges to urban analysis for supporting planning processes. This particularly applies to large urban events because their characteristics often contradict daily planning routines. Due to the availability of large amounts of data, social media offer the possibility for fine-scale spatial and temporal analysis in this context, especially regarding public emotions related to varied topics. Thus, this article proposes a combined approach for analyzing large sports events considering event days vs comparison days (before or after the event) and different user groups (residents vs visitors), as well as integrating sentiment analysis and topic extraction. Our results based on various analyses of tweets demonstrate that different spatial and temporal patterns can be identified, clearly distinguishing both residents and visitors, along with positive or negative sentiment. Furthermore, we could assign tweets to specific urban events or extract topics related to the transportation infrastructure. Although the results are potentially able to support urban planning processes of large events, the approach still shows some limitations including well-known biases in social media or shortcomings in identifying the user groups and in the topic modeling approach.

Suggested Citation

  • Anna Kovacs-Gyori & Alina Ristea & Clemens Havas & Bernd Resch & Pablo Cabrera-Barona, 2018. "#London2012: Towards Citizen-Contributed Urban Planning Through Sentiment Analysis of Twitter Data," Urban Planning, Cogitatio Press, vol. 3(1), pages 75-99.
    • Handle: RePEc:cog:urbpla:v3:y:2018:i:1:p:75-99
    DOI: 10.17645/up.v3i1.1287
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    References listed on IDEAS

    as
    1. Bernd Resch & Anja Summa & Peter Zeile & Michael Strube, 2016. "Citizen-Centric Urban Planning through Extracting Emotion Information from Twitter in an Interdisciplinary Space-Time-Linguistics Algorithm," Urban Planning, Cogitatio Press, vol. 1(2), pages 114-127.
    2. Costanza, Robert & Fisher, Brendan & Ali, Saleem & Beer, Caroline & Bond, Lynne & Boumans, Roelof & Danigelis, Nicholas L. & Dickinson, Jennifer & Elliott, Carolyn & Farley, Joshua & Gayer, Diane Elli, 2007. "Quality of life: An approach integrating opportunities, human needs, and subjective well-being," Ecological Economics, Elsevier, vol. 61(2-3), pages 267-276, March.
    3. Robert Cummins & Helen Nistico, 2002. "Maintaining Life Satisfaction: The Role of Positive Cognitive Bias," Journal of Happiness Studies, Springer, vol. 3(1), pages 37-69, March.
    4. Lewis Mitchell & Morgan R Frank & Kameron Decker Harris & Peter Sheridan Dodds & Christopher M Danforth, 2013. "The Geography of Happiness: Connecting Twitter Sentiment and Expression, Demographics, and Objective Characteristics of Place," PLOS ONE, Public Library of Science, vol. 8(5), pages 1-15, May.
    5. Bernd Resch & Anja Summa & Peter Zeile & Michael Strube, 2016. "Citizen-Centric Urban Planning through Extracting Emotion Information from Twitter in an Interdisciplinary Space-Time-Linguistics Algorithm," Urban Planning, Cogitatio Press, vol. 1(2), pages 114-127.
    6. Fernando Diaz & Michael Gamon & Jake M Hofman & Emre Kıcıman & David Rothschild, 2016. "Online and Social Media Data As an Imperfect Continuous Panel Survey," PLOS ONE, Public Library of Science, vol. 11(1), pages 1-21, January.
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