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

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.