Title |
Tweet for health: using an online social network to examine temporal trends in weight loss-related posts
|
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Published in |
Translational Behavioral Medicine, January 2015
|
DOI | 10.1007/s13142-015-0308-1 |
Pubmed ID | |
Authors |
Gabrielle M. Turner-McGrievy, Michael W. Beets |
Abstract |
Few studies have used social networking sites to track temporal trends in health-related posts, particularly around weight loss. To examine the temporal relationship of Twitter messages about weight loss over 1 year (2012). Temporal trends in #weightloss mentions and #fitness, #diet, and #health tweets which also had the word "weight" in them were examined using three a priori time periods: (1) holidays: pre-winter holidays, holidays, and post-holidays; (2) Season: winter and summer; and (3) New Year's: pre-New Year's and post-New Year's. Regarding #weightloss, there were 145 (95 % CI 79, 211) more posts/day during holidays and 143 (95 % CI 76, 209) more posts/day after holidays as compared to 480 pre-holiday posts/day; 232 (95 % CI 178, 286) more posts/day during the winter versus summer (441 posts/day); there was no difference in posts around New Year's. Examining social networks for trends in health-related posts may aid in timing interventions when individuals are more likely to be discussing weight loss. |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 7 | 35% |
United Kingdom | 2 | 10% |
Canada | 1 | 5% |
Unknown | 10 | 50% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 11 | 55% |
Scientists | 5 | 25% |
Practitioners (doctors, other healthcare professionals) | 3 | 15% |
Science communicators (journalists, bloggers, editors) | 1 | 5% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Spain | 1 | 1% |
United States | 1 | 1% |
Bahrain | 1 | 1% |
Canada | 1 | 1% |
Unknown | 64 | 94% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 11 | 16% |
Student > Master | 8 | 12% |
Student > Doctoral Student | 8 | 12% |
Researcher | 6 | 9% |
Student > Bachelor | 5 | 7% |
Other | 13 | 19% |
Unknown | 17 | 25% |
Readers by discipline | Count | As % |
---|---|---|
Nursing and Health Professions | 8 | 12% |
Psychology | 8 | 12% |
Computer Science | 7 | 10% |
Social Sciences | 7 | 10% |
Medicine and Dentistry | 5 | 7% |
Other | 10 | 15% |
Unknown | 23 | 34% |