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Social Media Data Analysis in Urban e-Planning

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  • Pilvi Nummi

    (Aalto University, School of Engineering, Department of Built Environment, Espoo, Finland)

Abstract

Computational social media data analysis (SMDA) is opening up new possibilities for participatory urban planning. The aim of this study is to analyse what kind of computational methods can be used to analyse social media data to inform urban planning. A descriptive literature review of recent case study articles reveal that in this context SMDA has been applied mainly to location based social media data, such as geo-tagged Tweets, photographs and check-in data. There were only a few studies concerning the use of non-place-based data. Based on this review SMDA can provide planners with local knowledge about people's opinions, experiences, feelings, behaviour, and about the city structure. However, integration of this knowledge in planning and decision-making has not been completely successful in any of the cases. By way of a conclusion, a planning-led categorization of the SMDA method's tools and analysis results is suggested.

Suggested Citation

  • Pilvi Nummi, 2017. "Social Media Data Analysis in Urban e-Planning," International Journal of E-Planning Research (IJEPR), IGI Global, vol. 6(4), pages 18-31, October.
    • Handle: RePEc:igg:jepr00:v:6:y:2017:i:4:p:18-31
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    File URL: http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/IJEPR.2017100102
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    Cited by:

    1. Fernando Santa & Roberto Henriques & Joaquín Torres-Sospedra & Edzer Pebesma, 2019. "A Statistical Approach for Studying the Spatio-Temporal Distribution of Geolocated Tweets in Urban Environments," Sustainability, MDPI, vol. 11(3), pages 1-29, January.
    2. Pilvi Nummi, 2018. "Crowdsourcing Local Knowledge with PPGIS and Social Media for Urban Planning to Reveal Intangible Cultural Heritage," Urban Planning, Cogitatio Press, vol. 3(1), pages 100-115.

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