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Mining Social Media to Measure Neighborhood Quality in the City of Atlanta

Mining Social Media to Measure Neighborhood Quality in the City of Atlanta
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Author(s): Subhrajit Guhathakurta (Center for Spatial Planning Analytics and Visualization, Georgia Institute of Technology, Atlanta, USA), Ge Zhang (Georgia Institute of Technology, Atlanta, USA), Guangxu Chen (Georgia Institute of Technology, Atlanta, USA), Caroline Burnette (Georgia Institute of Technology, Atlanta, USA)and Isabel Sepkowitz (Georgia Institute of Technology, Atlanta, USA)
Copyright: 2019
Volume: 8
Issue: 1
Pages: 18
Source title: International Journal of E-Planning Research (IJEPR)
Editor(s)-in-Chief: Carlos Nunes Silva (University of Lisbon, Portugal)
DOI: 10.4018/IJEPR.2019010101

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Abstract

This article presents a model to classify perceptions of various Atlanta neighborhoods based on social media. Tweets were extracted using Twitter's API and categorized to determine 1) whether they are neighborhood related; 2) whether a positive or negative sentiment could be assigned, and 3) whether they belong to one of eight categories of neighborhood quality assessments. These eight categories are public safety, transportation, density, walkability, maintenance, aesthetics, open space, and quality of dining and entertainment venues. Tweets that were related to neighborhood quality and geo-tagged accounted for 4% of all filtered Tweets. Overall 49% of neighborhood perception related Tweets were extracted to create an indicator of perceived neighborhood quality. The study then compared the perception of neighborhoods from social media analysis with quantitative indicators of neighborhood quality.

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