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- Publisher Website: 10.2105/AJPH.2017.303993
- Scopus: eid_2-s2.0-85031504634
- PMID: 28933925
- WOS: WOS:000419238700039
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Article: Geotagged US tweets as predictors of county-level health outcomes, 2015-2016
Title | Geotagged US tweets as predictors of county-level health outcomes, 2015-2016 |
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Authors | |
Issue Date | 2017 |
Citation | American Journal of Public Health, 2017, v. 107, n. 11, p. 1776-1782 How to Cite? |
Abstract | Objectives. To leverage geotagged Twitter data to create national indicators of the social environment, with small-area indicators of prevalent sentiment and social modeling of health behaviors, and to test associations with county-level health outcomes, while controlling for demographic characteristics. Methods. We used Twitter's streaming application programming interface to continuously collect a random 1% subset of publicly available geo-located tweets in the contiguous United States. We collected approximately 80 million geotagged tweets from 603 363 unique Twitter users in a 12-month period (April 2015-March 2016). Results. Across 3135 US counties, Twitter indicators of happiness, food, and physical activity were associated with lower premature mortality, obesity, and physical inactivity. Alcohol-use tweets predicted higher alcohol-use-related mortality. Conclusions. Socialmedia represents a newtype of real-time data thatmay enable public healthofficials toexaminemovement ofnorms, sentiment, andbehaviors thatmayportend emerging issues or outbreaks-thus providing a way to intervene to prevent adverse health events and measure the impact of health interventions. |
Persistent Identifier | http://hdl.handle.net/10722/324028 |
ISSN | 2023 Impact Factor: 9.6 2023 SCImago Journal Rankings: 2.139 |
ISI Accession Number ID |
DC Field | Value | Language |
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dc.contributor.author | Nguyen, Quynh C. | - |
dc.contributor.author | McCullough, Matt | - |
dc.contributor.author | Meng, Hsien Wen | - |
dc.contributor.author | Paul, Debjyoti | - |
dc.contributor.author | Li, Dapeng | - |
dc.contributor.author | Kath, Suraj | - |
dc.contributor.author | Loomis, Geoffrey | - |
dc.contributor.author | Nsoesie, Elaine O. | - |
dc.contributor.author | Wen, Ming | - |
dc.contributor.author | Smith, Ken R. | - |
dc.contributor.author | Li, Feifei | - |
dc.date.accessioned | 2023-01-13T03:01:00Z | - |
dc.date.available | 2023-01-13T03:01:00Z | - |
dc.date.issued | 2017 | - |
dc.identifier.citation | American Journal of Public Health, 2017, v. 107, n. 11, p. 1776-1782 | - |
dc.identifier.issn | 0090-0036 | - |
dc.identifier.uri | http://hdl.handle.net/10722/324028 | - |
dc.description.abstract | Objectives. To leverage geotagged Twitter data to create national indicators of the social environment, with small-area indicators of prevalent sentiment and social modeling of health behaviors, and to test associations with county-level health outcomes, while controlling for demographic characteristics. Methods. We used Twitter's streaming application programming interface to continuously collect a random 1% subset of publicly available geo-located tweets in the contiguous United States. We collected approximately 80 million geotagged tweets from 603 363 unique Twitter users in a 12-month period (April 2015-March 2016). Results. Across 3135 US counties, Twitter indicators of happiness, food, and physical activity were associated with lower premature mortality, obesity, and physical inactivity. Alcohol-use tweets predicted higher alcohol-use-related mortality. Conclusions. Socialmedia represents a newtype of real-time data thatmay enable public healthofficials toexaminemovement ofnorms, sentiment, andbehaviors thatmayportend emerging issues or outbreaks-thus providing a way to intervene to prevent adverse health events and measure the impact of health interventions. | - |
dc.language | eng | - |
dc.relation.ispartof | American Journal of Public Health | - |
dc.title | Geotagged US tweets as predictors of county-level health outcomes, 2015-2016 | - |
dc.type | Article | - |
dc.description.nature | link_to_subscribed_fulltext | - |
dc.identifier.doi | 10.2105/AJPH.2017.303993 | - |
dc.identifier.pmid | 28933925 | - |
dc.identifier.scopus | eid_2-s2.0-85031504634 | - |
dc.identifier.volume | 107 | - |
dc.identifier.issue | 11 | - |
dc.identifier.spage | 1776 | - |
dc.identifier.epage | 1782 | - |
dc.identifier.eissn | 1541-0048 | - |
dc.identifier.isi | WOS:000419238700039 | - |