| Sumario: | This paper explores the use of powerful new software tools and social media data that can be used to study the attitudes of people in urban places. In particular, it uses propensity scoring to develop matched pairs of mid-sized US cities in the North East and Midwest, where the most significant difference between each pair is that of population decline. This resulted in a group of fifty declining cities matched with fifty growing or stable cities. Over 300,000 Twitter posts were collected over the course of two months, each analysed for either positive or negative sentiment. After running difference-of-means tests, we found that sentiment in the declining cities does not differ in a statistically significant manner from that in stable and growing cities. These findings suggest that real opportunities exist the better to understand urban attitudes through sentiment analysis of Twitter data.
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