Estimating geographic subjective well-being from Twitter: A comparison of dictionary and data-driven language methods.

ABSTRACT: Researchers and policy makers worldwide are interested in measuring the subjective well-being of populations. When users post on social media, they leave behind digital traces that reflect their thoughts and feelings. Aggregation of such digital traces may make it possible to monitor well-being at large scale. However, social media-based methods need to be robust to regional effects if they are to produce reliable estimates. Using a sample of 1.53 billion geotagged English tweets, we provide a systematic evaluation of word-level and data-driven methods for text analysis for generating well-being estimates for 1,208 US counties. We compared Twitter-based county-level estimates with well-being measurements provided by the Gallup-Sharecare Well-Being Index survey through 1.73 million phone su

SUBMITTER: Jaidka K 

PROVIDER: S-EPMC7229753 | biostudies-literature | 2020 May

REPOSITORIES: biostudies-literature