{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,14]],"date-time":"2026-02-14T13:19:49Z","timestamp":1771075189477,"version":"3.50.1"},"reference-count":51,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2021,9,9]],"date-time":"2021-09-09T00:00:00Z","timestamp":1631145600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2021,9,9]],"date-time":"2021-09-09T00:00:00Z","timestamp":1631145600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"funder":[{"name":"MassMutual"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["J Big Data"],"published-print":{"date-parts":[[2021,12]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:p>Sleep loss has been linked to heart disease, diabetes, cancer, and an increase in accidents, all of which are among the leading causes of death in the United States. Population-scale sleep studies have the potential to advance public health by helping to identify at-risk populations, changes in collective sleep patterns, and to inform policy change. Prior research suggests other kinds of health indicators such as depression and obesity can be estimated using social media activity. However, the inability to effectively measure collective sleep with publicly available data has limited large-scale academic studies. Here, we investigate the passive estimation of sleep loss through a proxy analysis of Twitter activity profiles. We use \u201cSpring Forward\u201d events, which occur at the beginning of Daylight Savings Time in the United States, as a natural experimental condition to estimate spatial differences in sleep loss across the United States. On average, peak Twitter activity occurs 15 to 30 min later on the Sunday following Spring Forward. By Monday morning however, activity curves are realigned with the week before, suggesting that the window of sleep opportunity is compressed in Twitter data, revealing Spring Forward behavioral change.<\/jats:p>","DOI":"10.1186\/s40537-021-00503-0","type":"journal-article","created":{"date-parts":[[2021,9,9]],"date-time":"2021-09-09T09:02:47Z","timestamp":1631178167000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["The sleep loss insult of Spring Daylight Savings in the US is observable in Twitter activity"],"prefix":"10.1186","volume":"8","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5724-0900","authenticated-orcid":false,"given":"Kelsey","family":"Linnell","sequence":"first","affiliation":[]},{"given":"Michael","family":"Arnold","sequence":"additional","affiliation":[]},{"given":"Thayer","family":"Alshaabi","sequence":"additional","affiliation":[]},{"given":"Thomas","family":"McAndrew","sequence":"additional","affiliation":[]},{"given":"Jeanie","family":"Lim","sequence":"additional","affiliation":[]},{"given":"Peter Sheridan","family":"Dodds","sequence":"additional","affiliation":[]},{"given":"Christopher M.","family":"Danforth","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2021,9,9]]},"reference":[{"issue":"8","key":"503_CR1","doi-asserted-by":"publisher","first-page":"1161","DOI":"10.5665\/sleep.4886","volume":"38","author":"CC Panel","year":"2015","unstructured":"Panel CC, Watson NF, Badr MS, Belenky G, Bliwise DL, Buxton OM, et al. Joint consensus statement of the American Academy of Sleep Medicine and Sleep Research Society on the recommended amount of sleep for a healthy adult: Methodology and discussion. Sleep. 2015;38(8):1161\u201383.","journal-title":"Sleep."},{"key":"503_CR2","unstructured":"Short Sleep Duration Among US Adults; 2017."},{"issue":"5","key":"503_CR3","doi-asserted-by":"publisher","first-page":"829","DOI":"10.5665\/sleep.4684","volume":"38","author":"ES Ford","year":"2015","unstructured":"Ford ES, Cunningham TJ, Croft JB. Trends in self-reported sleep duration among US adults from 1985 to 2012. Sleep. 2015;38(5):829\u201332.","journal-title":"Sleep."},{"key":"503_CR4","doi-asserted-by":"crossref","unstructured":"Althoff T, Horvitz E, White RW, Zeitzer J. Harnessing the web for population-scale physiological sensing: a case study of sleep and performance. In: WWW \u201917 Proceedings of the 26th International Conference on World Wide Web. 2017; p. 113\u201322.","DOI":"10.1145\/3038912.3052637"},{"issue":"5","key":"503_CR5","doi-asserted-by":"publisher","first-page":"323","DOI":"10.1016\/j.smrv.2005.11.001","volume":"10","author":"G Curcio","year":"2006","unstructured":"Curcio G, Ferrara M, De Gennaro L. Sleep loss, learning capacity and academic performance. Sleep Med Rev. 2006;10(5):323\u201337.","journal-title":"Sleep Med Rev"},{"issue":"4","key":"503_CR6","doi-asserted-by":"publisher","first-page":"213","DOI":"10.1016\/j.slsci.2014.11.001","volume":"7","author":"M Engle-Friedman","year":"2014","unstructured":"Engle-Friedman M. The effects of sleep loss on capacity and effort. Sleep Sci. 2014;7(4):213\u201324.","journal-title":"Sleep Sci"},{"issue":"1","key":"503_CR7","doi-asserted-by":"publisher","first-page":"91","DOI":"10.1097\/JOM.0b013e3181c78c30","volume":"52","author":"MR Rosekind","year":"2010","unstructured":"Rosekind MR, Gregory KB, Mallis MM, Brandt SL, Seal B, Lerner D. The cost of poor sleep: workplace productivity loss and associated costs. J Occup Environ Med. 2010;52(1):91\u20138.","journal-title":"J Occup Environ Med"},{"issue":"2","key":"503_CR8","doi-asserted-by":"publisher","first-page":"144","DOI":"10.1097\/JOM.0b013e3181c99505","volume":"52","author":"B Dean","year":"2010","unstructured":"Dean B, Aguilar D, Shapiro C, Orr WC, Isserman JA, Calimlim B, et al. Impaired health status, daily functioning, and work productivity in adults with excessive sleepiness. J Occup Environ Med. 2010;52(2):144\u20139.","journal-title":"J Occup Environ Med"},{"key":"503_CR9","unstructured":"Owens J, Dingus T, Guo F, Fang Y, Perez M, McClafferty J, et al. Prevalence of drowsy-driving crashes: Estimates from a large-scale naturalistic driving study. AAA Foundation for Traffic Safety. 2018."},{"issue":"2","key":"503_CR10","doi-asserted-by":"publisher","first-page":"zsx195","DOI":"10.1093\/sleep\/zsy061.520","volume":"41","author":"C Anderson","year":"2018","unstructured":"Anderson C, Ftouni S, Ronda JM, Rajaratnam SM, Czeisler CA, Lockley SW. Self-reported drowsiness and safety outcomes while driving after an extended duration work shift in trainee physicians. Sleep. 2018;41(2):zsx195.","journal-title":"Sleep."},{"key":"503_CR11","doi-asserted-by":"publisher","first-page":"151","DOI":"10.2147\/NSS.S134864","volume":"9","author":"G Medic","year":"2017","unstructured":"Medic G, Wille M, Hemels ME. Short-and long-term health consequences of sleep disruption. Nat Sci Sleep. 2017;9:151.","journal-title":"Nat Sci Sleep"},{"issue":"1","key":"503_CR12","doi-asserted-by":"publisher","first-page":"54","DOI":"10.2174\/157340310790231635","volume":"6","author":"M Nagai","year":"2010","unstructured":"Nagai M, Hoshide S, Kario K. Sleep duration as a risk factor for cardiovascular disease-a review of the recent literature. Curr Cardiol Rev. 2010;6(1):54\u201361.","journal-title":"Curr Cardiol Rev"},{"issue":"4","key":"503_CR13","doi-asserted-by":"publisher","first-page":"434","DOI":"10.1111\/anae.14533","volume":"74","author":"V Cheung","year":"2019","unstructured":"Cheung V, Yuen V, Wong G, Choi S. The effect of sleep deprivation and disruption on DNA damage and health of doctors. Anaesthesia. 2019;74(4):434\u201340.","journal-title":"Anaesthesia"},{"key":"503_CR14","unstructured":"Fox M. Shift work may cause cancer, world agency says. Reuters. 2007."},{"issue":"1","key":"503_CR15","doi-asserted-by":"publisher","first-page":"475","DOI":"10.1186\/1471-2458-10-475","volume":"10","author":"NP Patel","year":"2010","unstructured":"Patel NP, Grandner MA, Xie D, Branas CC, Gooneratne N. \u201cSleep disparity\u201d in the population: poor sleep quality is strongly associated with poverty and ethnicity. BMC Public Health. 2010;10(1):475.","journal-title":"BMC Public Health"},{"issue":"6","key":"503_CR16","doi-asserted-by":"publisher","first-page":"1053","DOI":"10.1007\/s40615-019-00607-7","volume":"6","author":"VK Chattu","year":"2019","unstructured":"Chattu VK, Chattu SK, Spence DW, Manzar MD, Burman D, Pandi-Perumal SR. Do disparities in sleep duration among racial and ethnic minorities contribute to differences in disease prevalence? J Racial Ethnic Health Disparit. 2019;6(6):1053\u201361.","journal-title":"J Racial Ethnic Health Disparit"},{"issue":"3","key":"503_CR17","doi-asserted-by":"publisher","first-page":"209","DOI":"10.1016\/j.sleep.2010.12.010","volume":"12","author":"ME Ruiter","year":"2011","unstructured":"Ruiter ME, DeCoster J, Jacobs L, Lichstein KL. Normal sleep in African-Americans and Caucasian-Americans: a meta-analysis. Sleep Med. 2011;12(3):209\u201314.","journal-title":"Sleep Med"},{"issue":"33","key":"503_CR18","doi-asserted-by":"publisher","first-page":"8889","DOI":"10.1073\/pnas.1618167114","volume":"114","author":"DS Curtis","year":"2017","unstructured":"Curtis DS, Fuller-Rowell TE, El-Sheikh M, Carnethon MR, Ryff CD. Habitual sleep as a contributor to racial differences in cardiometabolic risk. Proc Nat Acad Sci. 2017;114(33):8889\u201394.","journal-title":"Proc Nat Acad Sci"},{"issue":"4","key":"503_CR19","first-page":"11","volume":"6","author":"M Hafner","year":"2017","unstructured":"Hafner M, Stepanek M, Taylor J, Troxel WM, Van Stolk C. Why sleep matters-the economic costs of insufficient sleep: a cross-country comparative analysis. Rand Health Q. 2017;6(4):11.","journal-title":"Rand Health Q"},{"key":"503_CR20","doi-asserted-by":"publisher","first-page":"99","DOI":"10.1016\/j.metabol.2017.10.008","volume":"84","author":"MT Bianchi","year":"2018","unstructured":"Bianchi MT. Sleep devices: wearables and nearables, informational and interventional, consumer and clinical. Metabolism. 2018;84:99\u2013108.","journal-title":"Metabolism"},{"issue":"8789","key":"503_CR21","doi-asserted-by":"publisher","first-page":"347","DOI":"10.1016\/0140-6736(92)91660-Z","volume":"339","author":"NJ Douglas","year":"1992","unstructured":"Douglas NJ, Thomas S, Jan MA. Clinical value of polysomnography. Lancet. 1992;339(8789):347\u201350.","journal-title":"Lancet"},{"issue":"1","key":"503_CR22","doi-asserted-by":"publisher","first-page":"77","DOI":"10.1037\/a0025730","volume":"138","author":"AG Harvey","year":"2012","unstructured":"Harvey AG, Tang NK. (Mis) perception of sleep in insomnia: a puzzle and a resolution. Psychol Bull. 2012;138(1):77.","journal-title":"Psychol Bull"},{"key":"503_CR23","doi-asserted-by":"publisher","first-page":"838","DOI":"10.1097\/EDE.0b013e318187a7b0","volume":"19","author":"DS Lauderdale","year":"2008","unstructured":"Lauderdale DS, Knutson KL, Yan LL, Liu K, Rathouz PJ. Self-reported and measured sleep duration: how similar are they? Epidemiology. 2008;19:838\u201345.","journal-title":"Epidemiology"},{"issue":"11","key":"503_CR24","doi-asserted-by":"publisher","first-page":"1747","DOI":"10.5665\/sleep.3142","volume":"36","author":"M Marino","year":"2013","unstructured":"Marino M, Li Y, Rueschman MN, Winkelman JW, Ellenbogen J, Solet JM, et al. Measuring sleep: accuracy, sensitivity, and specificity of wrist actigraphy compared to polysomnography. Sleep. 2013;36(11):1747\u201355.","journal-title":"Sleep."},{"key":"503_CR25","doi-asserted-by":"publisher","DOI":"10.1093\/sleep\/zsaa169","author":"SS Jonasdottir","year":"2021","unstructured":"Jonasdottir SS, Minor K, Lehmann S. Gender differences in nighttime sleep patterns and variability across the adult lifespan: a global-scale wearables study. Sleep. 2021. https:\/\/doi.org\/10.1093\/sleep\/zsaa169.","journal-title":"Sleep."},{"key":"503_CR26","doi-asserted-by":"publisher","first-page":"53","DOI":"10.1109\/RBME.2018.2811735","volume":"11","author":"S Roomkham","year":"2018","unstructured":"Roomkham S, Lovell D, Cheung J, Perrin D. Promises and challenges in the use of consumer-grade devices for sleep monitoring. IEEE Rev Biomed Eng. 2018;11:53\u201367.","journal-title":"IEEE Rev Biomed Eng"},{"issue":"23","key":"503_CR27","doi-asserted-by":"publisher","first-page":"3763","DOI":"10.1016\/j.cub.2018.10.016","volume":"28","author":"E Leypunskiy","year":"2018","unstructured":"Leypunskiy E, K\u0131c\u0131man E, Shah M, Walch OJ, Rzhetsky A, Dinner AR, et al. Geographically resolved rhythms in Twitter use reveal social pressures on daily activity patterns. Curr Biol. 2018;28(23):3763\u201375.","journal-title":"Curr Biol"},{"issue":"11","key":"503_CR28","doi-asserted-by":"publisher","first-page":"e0165331","DOI":"10.1371\/journal.pone.0165331","volume":"11","author":"MA Christensen","year":"2016","unstructured":"Christensen MA, Bettencourt L, Kaye L, Moturu ST, Nguyen KT, Olgin JE, et al. Direct measurements of smartphone screen-time: relationships with demographics and sleep. PLoS ONE. 2016;11(11):e0165331.","journal-title":"PLoS ONE"},{"key":"503_CR29","unstructured":"Rios M, Lin J. Visualizing the pulse of world cities on Twitter. In: Proceedings of the Seventh International AAAI Conference on Weblogs and Social Media; p.\u00a04."},{"issue":"17","key":"503_CR30","doi-asserted-by":"publisher","first-page":"R830","DOI":"10.1016\/j.cub.2017.08.005","volume":"27","author":"T Roenneberg","year":"2017","unstructured":"Roenneberg T. Twitter as a means to study temporal behaviour. Curr Biol. 2017;27(17):R830\u20132. https:\/\/doi.org\/10.1016\/j.cub.2017.08.005.","journal-title":"Curr Biol"},{"key":"503_CR31","unstructured":"Scheffler T, Kyba CCM. Measuring Social Jetlag in Twitter Data. In: Proceedings of the Tenth International AAAI Conference on Web and Social Media (ICWSM 2016); p. 4."},{"issue":"12","key":"503_CR32","doi-asserted-by":"publisher","first-page":"e26752","DOI":"10.1371\/journal.pone.0026752","volume":"6","author":"PS Dodds","year":"2011","unstructured":"Dodds PS, Harris KD, Kloumann IM, Bliss CA, Danforth CM. Temporal patterns of happiness and information in a global social network: Hedonometrics and Twitter. PLoS ONE. 2011;6(12):e26752.","journal-title":"PLoS ONE"},{"issue":"2","key":"503_CR33","doi-asserted-by":"publisher","first-page":"e0168893","DOI":"10.1371\/journal.pone.0168893","volume":"12","author":"SE Alajajian","year":"2017","unstructured":"Alajajian SE, Williams JR, Reagan AJ, Alajajian SC, Frank MR, Mitchell L, et al. The Lexicocalorimeter: Gauging public health through caloric input and output on social media. PLoS ONE. 2017;12(2):e0168893.","journal-title":"PLoS ONE."},{"key":"503_CR34","doi-asserted-by":"publisher","first-page":"239821281774450","DOI":"10.1177\/2398212817744501","volume":"1","author":"F Dzogang","year":"2017","unstructured":"Dzogang F, Lightman S, Cristianini N. Circadian mood variations in Twitter content. Brain Neurosci Adv. 2017;1:2398212817744501. https:\/\/doi.org\/10.1177\/2398212817744501.","journal-title":"Brain Neurosci Adv"},{"issue":"6","key":"503_CR35","doi-asserted-by":"publisher","first-page":"e0197002","DOI":"10.1371\/journal.pone.0197002","volume":"13","author":"F Dzogang","year":"2018","unstructured":"Dzogang F, Lightman S, Cristianini N. Diurnal variations of psychometric indicators in Twitter content. PLoS ONE. 2018;13(6):e0197002. https:\/\/doi.org\/10.1371\/journal.pone.0197002.","journal-title":"PLoS ONE"},{"issue":"6","key":"503_CR36","doi-asserted-by":"publisher","first-page":"e140","DOI":"10.2196\/jmir.4476","volume":"17","author":"DJ McIver","year":"2015","unstructured":"McIver DJ, Hawkins JB, Chunara R, Chatterjee AK, Bhandari A, Fitzgerald TP, et al. Characterizing sleep issues using Twitter. J Med Internet Res. 2015;17(6):e140.","journal-title":"J Med Internet Res"},{"issue":"1","key":"503_CR37","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1038\/s41598-018-37186-2","volume":"9","author":"JM Mart\u00edn-Olalla","year":"2019","unstructured":"Mart\u00edn-Olalla JM. The long term impact of daylight saving time regulations in daily life at several circles of latitude. Sci Rep. 2019;9(1):1\u201313.","journal-title":"Sci Rep"},{"key":"503_CR38","doi-asserted-by":"publisher","DOI":"10.1111\/jsr.12916","author":"JM Mart\u00edn-Olalla","year":"2019","unstructured":"Mart\u00edn-Olalla JM. Scandinavian bed and rise times in the Age of Enlightenment and in the 21st century show similarity, helped by Daylight Saving Time. J Sleep Res. 2019. https:\/\/doi.org\/10.1111\/jsr.12916.","journal-title":"J Sleep Res."},{"issue":"22","key":"503_CR39","doi-asserted-by":"publisher","first-page":"1996","DOI":"10.1016\/j.cub.2007.10.025","volume":"17","author":"T Kantermann","year":"2007","unstructured":"Kantermann T, Juda M, Merrow M, Roenneberg T. The Human Circadian Clock\u2019s seasonal adjustment is disrupted by daylight saving time. Curr Biol. 2007;17(22):1996\u20132000. https:\/\/doi.org\/10.1016\/j.cub.2007.10.025.","journal-title":"Curr Biol"},{"issue":"1","key":"503_CR40","doi-asserted-by":"publisher","first-page":"e000019","DOI":"10.1136\/openhrt-2013-000019","volume":"1","author":"A Sandhu","year":"2014","unstructured":"Sandhu A, Seth M, Gurm HS. Daylight Savings Time and myocardial infarction. Open Heart. 2014;1(1):e000019.","journal-title":"Open Heart"},{"key":"503_CR41","doi-asserted-by":"publisher","first-page":"20","DOI":"10.1016\/j.sleep.2016.10.009","volume":"27","author":"JO Sipil\u00e4","year":"2016","unstructured":"Sipil\u00e4 JO, Ruuskanen JO, Rautava P, Kyt\u00f6 V. Changes in ischemic stroke occurrence following Daylight Saving Time transitions. Sleep Med. 2016;27:20\u20134.","journal-title":"Sleep Med"},{"issue":"1","key":"503_CR42","doi-asserted-by":"publisher","first-page":"31","DOI":"10.1016\/S1389-9457(00)00032-0","volume":"2","author":"J Varughese","year":"2001","unstructured":"Varughese J, Allen RP. Fatal accidents following changes in Daylight Savings Time: The American experience. Sleep Med. 2001;2(1):31\u20136.","journal-title":"Sleep Med"},{"issue":"7","key":"503_CR43","doi-asserted-by":"publisher","first-page":"R298","DOI":"10.1016\/j.cub.2020.03.007","volume":"30","author":"JM Mart\u00edn-Olalla","year":"2020","unstructured":"Mart\u00edn-Olalla JM. Traffic accident increase attributed to Daylight Saving Time doubled after Energy Policy Act. Curr Biol. 2020;30(7):R298\u2013300. https:\/\/doi.org\/10.1016\/j.cub.2020.03.007.","journal-title":"Curr Biol"},{"issue":"4","key":"503_CR44","doi-asserted-by":"publisher","first-page":"1005","DOI":"10.1257\/aer.90.4.1005","volume":"90","author":"MJ Kamstra","year":"2000","unstructured":"Kamstra MJ, Kramer LA, Levi MD. Losing sleep at the market: The Daylight Saving anomaly. Am Econ Rev. 2000;90(4):1005\u201311.","journal-title":"Am Econ Rev"},{"issue":"12","key":"503_CR45","doi-asserted-by":"publisher","first-page":"e0209651","DOI":"10.1371\/journal.pone.0209651","volume":"13","author":"TJ Gray","year":"2018","unstructured":"Gray TJ, Reagan AJ, Dodds PS, Danforth CM. English verb regularization in books and tweets. PLoS ONE. 2018;13(12):e0209651.","journal-title":"PLoS ONE"},{"key":"503_CR46","unstructured":"Twitter. Developer application program interface (API); 2020. https:\/\/developer.twitter.com\/en\/docs\/tweets\/sample-realtime\/overview\/decahose."},{"key":"503_CR47","doi-asserted-by":"crossref","unstructured":"Rasmussen CE. Gaussian processes in machine learning. In: summer school on machine learning. Springer; 2003. p. 63\u201371.","DOI":"10.1007\/978-3-540-28650-9_4"},{"issue":"Oct","key":"503_CR48","first-page":"2825","volume":"12","author":"F Pedregosa","year":"2011","unstructured":"Pedregosa F, Varoquaux G, Gramfort A, Michel V, Thirion B, Grisel O, et al. Scikit-learn: machine learning in Python. J Mach Learn Res. 2011;12(Oct):2825\u201330.","journal-title":"J Mach Learn Res"},{"key":"503_CR49","unstructured":"Inc PT. Collaborative data science; 2015. https:\/\/plot.ly."},{"key":"503_CR50","unstructured":"Wojcik S, Hughes A. Sizing up Twitter users; 2019."},{"key":"503_CR51","unstructured":"DeGeneres E; March 2, 2014. https:\/\/twitter.com\/theellenshow\/status\/440322224407314432."}],"container-title":["Journal of Big Data"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1186\/s40537-021-00503-0.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1186\/s40537-021-00503-0\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1186\/s40537-021-00503-0.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,1,8]],"date-time":"2023-01-08T21:57:55Z","timestamp":1673215075000},"score":1,"resource":{"primary":{"URL":"https:\/\/journalofbigdata.springeropen.com\/articles\/10.1186\/s40537-021-00503-0"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,9,9]]},"references-count":51,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2021,12]]}},"alternative-id":["503"],"URL":"https:\/\/doi.org\/10.1186\/s40537-021-00503-0","relation":{},"ISSN":["2196-1115"],"issn-type":[{"value":"2196-1115","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,9,9]]},"assertion":[{"value":"8 April 2021","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"20 August 2021","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"9 September 2021","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"Research using aggregate Twitter data was approved for IRB exemption by UVM under protocol 15-571: Building an Instrument that Measures Health, Well-Being, and Disease in Real-Time.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethics approval and consent to participate"}},{"value":"Not applicable.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Consent to participate"}},{"value":"The authors are unaware of any competing interests at this time.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}],"article-number":"121"}}