{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,9]],"date-time":"2026-09-09T18:07:02Z","timestamp":1788977222264,"version":"build-2803163510"},"reference-count":56,"publisher":"Public Library of Science (PLoS)","issue":"9","license":[{"start":{"date-parts":[[2026,9,9]],"date-time":"2026-09-09T00:00:00Z","timestamp":1788912000000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"University of New Mexico Office of the Vice President for Research","award":["WeR1 Faculty Success Program"],"award-info":[{"award-number":["WeR1 Faculty Success Program"]}]},{"name":"University of New Mexico Office of the Vice President for Research","award":["Research Allocations Committee (RAC) awards (#8oh6a4x35h)"],"award-info":[{"award-number":["Research Allocations Committee (RAC) awards (#8oh6a4x35h)"]}]},{"name":"University of New Mexico Office of the Vice President for Research","award":["Research Allocations Committee (RAC) awards (#gvvrxwyj64)"],"award-info":[{"award-number":["Research Allocations Committee (RAC) awards (#gvvrxwyj64)"]}]},{"name":"University of New Mexico Office of the Vice President for Research","award":["FRESSH Pilot Program"],"award-info":[{"award-number":["FRESSH Pilot Program"]}]},{"name":"University of New Mexico, A&S Interdisciplinary Science Cooperative through the Office of Research","award":["Faculty Team Research Concept Competition Award #TA-1003"],"award-info":[{"award-number":["Faculty Team Research Concept Competition Award #TA-1003"]}]},{"name":"Rising Researcher award from Penn State\u2019s Institute for Computational and Data Sciences","award":["RRID:SCR_025154"],"award-info":[{"award-number":["RRID:SCR_025154"]}]}],"content-domain":{"domain":["www.plosone.org"],"crossmark-restriction":false},"short-container-title":["PLoS One"],"abstract":"<jats:p>Sleeplessness is a widespread public health concern that was further intensified during the COVID-19 pandemic, yet large-scale, real-time monitoring of sleep disturbance remains limited. This study introduces a scalable social sensing framework that leverages temporally filtered nighttime social media activity (10:00 p.m. - 6:00 a.m. local time) to infer population-level patterns of sleep disturbance. To demonstrate the framework, we conducted a comprehensive analysis of geotagged tweets posted by users in the United States from March 1, 2020 to June 30, 2021, using pre-pandemic tweets as a baseline for comparison. Spatial, temporal, sentiment, and topical patterns were analyzed to characterize nighttime sleep disturbances at the U.S. state level. Three distinct temporal patterns of nighttime disturbance were identified during the pandemic, including single peak, multiple peaks, and smooth patterns, indicating heterogeneous impacts across states. Correlations between nighttime tweet ratios and daily new COVID-19 case counts varied across states and pandemic stages. In addition, more negative emotions expressed in nighttime tweets were associated with increased sleep disturbance. Nighttime tweets were more likely to focus on local news and events. Greater topical diversity among the population was associated with reduced negative emotional impacts during the pandemic. Overall, the findings demonstrate that nighttime social media data provide an effective and scalable social sensing approach for examining population-level patterns of potential sleep disturbance across large geographic regions and extended time periods. Beyond sleep-related applications, this framework offers a transferable method for monitoring other forms of nighttime human activity and broader social dynamics, including crime, disaster response, and social unrest.<\/jats:p>","DOI":"10.1371\/journal.pone.0356547","type":"journal-article","created":{"date-parts":[[2026,9,9]],"date-time":"2026-09-09T17:22:50Z","timestamp":1788974570000},"page":"e0356547","update-policy":"https:\/\/doi.org\/10.1371\/journal.pone.corrections_policy","source":"Crossref","is-referenced-by-count":0,"title":["Sleepless in America: A social sensing study of pandemic-era sleeplessness using nighttime social media data"],"prefix":"10.1371","volume":"21","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-7899-6213","authenticated-orcid":true,"given":"Xi","family":"Gong","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0008-4312-7411","authenticated-orcid":true,"given":"Lin","family":"Liu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yujian","family":"Lu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Guiming","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4323-382X","authenticated-orcid":true,"given":"Xiao","family":"Huang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yan","family":"Lin","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"340","published-online":{"date-parts":[[2026,9,9]]},"reference":[{"key":"pone.0356547.ref001","doi-asserted-by":"crossref","DOI":"10.3109\/9781420080803","volume-title":"Insomnia: Diagnosis and treatment","author":"MJ Sateia","year":"2016"},{"issue":"5","key":"pone.0356547.ref002","doi-asserted-by":"crossref","first-page":"829","DOI":"10.5665\/sleep.4684","article-title":"Trends in self-reported sleep duration among US adults from 1985 to 2012","volume":"38","author":"ES Ford","year":"2015","journal-title":"Sleep"},{"issue":"2","key":"pone.0356547.ref003","doi-asserted-by":"crossref","first-page":"344","DOI":"10.1007\/s10900-011-9451-x","article-title":"Household demographics and perceived insufficient sleep among US adults","volume":"37","author":"DP Chapman","year":"2012","journal-title":"J Community Health"},{"key":"pone.0356547.ref004","doi-asserted-by":"crossref","first-page":"84","DOI":"10.1186\/1471-2458-13-84","article-title":"Association between perceived insufficient sleep, frequent mental distress, obesity and chronic diseases among US adults, 2009 behavioral risk factor surveillance system","volume":"13","author":"Y Liu","year":"2013","journal-title":"BMC Public Health"},{"issue":"5","key":"pone.0356547.ref005","first-page":"873","article-title":"Economic effects of insomnia","volume":"16","author":"MK Stoller","year":"1994","journal-title":"Clin Ther"},{"issue":"17","key":"pone.0356547.ref006","doi-asserted-by":"crossref","first-page":"6401","DOI":"10.3390\/ijerph17176401","article-title":"Insomnia Interventions in the Workplace: A Systematic Review and Meta-Analysis","volume":"17","author":"J Vega-Esca\u00f1o","year":"2020","journal-title":"Int J Environ Res Public Health"},{"issue":"5","key":"pone.0356547.ref007","doi-asserted-by":"crossref","first-page":"470","DOI":"10.1016\/j.sleep.2009.10.006","article-title":"Who gets the best sleep? 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