Investigating the Emotional Responses of Individuals to Urban Green Space Using Twitter Data: A Critical Comparison of Three Different Methods of Sentiment Analysis

Helen Roberts, Bernd Resch, Jon Sadler, Lee Chapman, Andreas Petutschnig and Stefan Zimmer
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Helen Roberts: School of Geography, Earth and Environmental Sciences, University of Birmingham, UK
Bernd Resch: Department of Geoinformatics, University of Salzburg, Austria / Center for Geographic Analysis, Harvard University, USA
Jon Sadler: School of Geography, Earth and Environmental Sciences, University of Birmingham, UK
Lee Chapman: School of Geography, Earth and Environmental Sciences, University of Birmingham, UK
Andreas Petutschnig: Department of Geoinformatics, University of Salzburg, Austria
Stefan Zimmer: Department of Geoinformatics, University of Salzburg, Austria

Urban Planning, 2018, vol. 3, issue 1, 21-33

Abstract: In urban research, Twitter data have the potential to provide additional information about urban citizens, their activities, mobility patterns and emotion. Extracting the sentiment present in tweets is increasingly recognised as a valuable approach to gathering information on the mood, opinion and emotional responses of individuals in a variety of contexts. This article evaluates the potential of deriving emotional responses of individuals while they experience and interact with urban green space. A corpus of over 10,000 tweets relating to 60 urban green spaces in Birmingham, United Kingdom was analysed for positivity, negativity and specific emotions, using manual, semi-automated and automated methods of sentiment analysis and the outputs of each method compared. Similar numbers of tweets were annotated as positive/neutral/negative by all three methods; however, inter-method consistency in tweet assignment between the methods was low. A comparison of all three methods on the same corpus of tweets, using character emojis as an additional quality control, identifies a number of limitations associated with each approach. The results presented have implications for urban planners in terms of the choices available to identify and analyse the sentiment present in tweets, and the importance of choosing the most appropriate method. Future attempts to develop more reliable and accurate algorithms of sentiment analysis are needed and should focus on semi-automated methods.

Keywords: emotions; sentiment analysis; Twitter; urban green space; urban planning (search for similar items in EconPapers)
Date: 2018
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Persistent link: https://EconPapers.repec.org/RePEc:cog:urbpla:v3:y:2018:i:1:p:21-33

DOI: 10.17645/up.v3i1.1231

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