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Spatial Distribution of City Tweets and Their Densities
University of Gävle, Faculty of Engineering and Sustainable Development, Department of Computer and Geospatial Sciences, Geospatial Sciences.ORCID iD: 0000-0002-2337-2486
University of Gävle, Faculty of Engineering and Sustainable Development, Department of Computer and Geospatial Sciences, Geospatial Sciences.ORCID iD: 0000-0001-9328-9584
University of Gävle, Faculty of Engineering and Sustainable Development, Department of Building Engineering, Energy Systems and Sustainability Science, Energy Systems and Building Technology.ORCID iD: 0000-0003-1121-2394
2021 (English)In: Urban Remote Sensing: Monitoring, Synthesis, and Modeling in the Urban Environment, John Wiley & Sons, 2021, 2, p. 115-129Chapter in book (Other academic)
Abstract [en]

Social media outlets such as Twitter constitute valuable data sources for understanding human activities in the virtual world from a geographic perspective. This paper examines spatial distribution of tweets and densities within cities. The cities refer to natural cities that are automatically aggregated from a country's small street blocks, the so-called city blocks. We adopted street blocks (rather than census tracts) as the basic geographic units and topological center (rather than geometric center) in order to assess how tweets and densities vary from the center to the peripheral border. We found that, within a city from the center to the periphery, the tweets first increase and then decrease, while the densities decrease in general. These increases and decreases fluctuate dramatically and differ significantly from those if census tracts are used as the basic geographic units. We also found that the decrease of densities from the center to the periphery is less significant, and even disappears, if an arbitrarily defined city border is adopted. These findings prove that natural cities and their topological centers are better than their counterparts (conventionally defined cities and city centers) for geographic research. Based on this study, we believe that tweet densities can be a good surrogate of population densities. If this belief is proved to be true, social media data could help solve the dispute surrounding exponential or power function of urban population density. 

Place, publisher, year, edition, pages
John Wiley & Sons, 2021, 2. p. 115-129
National Category
Civil Engineering
Identifiers
URN: urn:nbn:se:hig:diva-42990DOI: 10.1002/9781119625865.ch6Scopus ID: 2-s2.0-85127672944ISBN: 9781119625841 (print)ISBN: 9781119625865 (electronic)OAI: oai:DiVA.org:hig-42990DiVA, id: diva2:1795889
Available from: 2023-09-11 Created: 2023-09-11 Last updated: 2023-09-11Bibliographically approved

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Jiang, BinMa, DingSandberg, Mats

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