This paper is in the following e-collection/theme issue:

JMIR Theme Issue: COVID-19 Special Issue (2394) Infodemiology and Infoveillance (1278) Medicine 2.0: Social Media, Open, Participatory, Collaborative Medicine (1573) Infoveillance, Infodemiology, Digital Disease Surveillance, Infodemic Management (1015) Outbreak and Pandemic Preparedness and Management (1679) Theme Issue: Novel Coronavirus (COVID-19) Outbreak Rapid Reports (1484) JMH Theme Issue: COVID-19 and Mental Health: Impact and Interventions (374)

Published on in Vol 22, No 12 (2020): December

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/21418, first published .
Social Media Insights Into US Mental Health During the COVID-19 Pandemic: Longitudinal Analysis of Twitter Data

Social Media Insights Into US Mental Health During the COVID-19 Pandemic: Longitudinal Analysis of Twitter Data

Social Media Insights Into US Mental Health During the COVID-19 Pandemic: Longitudinal Analysis of Twitter Data

Authors of this article:

Danny Valdez1 Author Orcid Image ;   Marijn ten Thij2 Author Orcid Image ;   Krishna Bathina2 Author Orcid Image ;   Lauren A Rutter3 Author Orcid Image ;   Johan Bollen2 Author Orcid Image
Article Authors Cited by (162) Tweetations (14) Metrics

Journals

  1. Chum A, Nielsen A, Bellows Z, Farrell E, Durette P, Banda J, Cupchik G. Changes in Public Response Associated With Various COVID-19 Restrictions in Ontario, Canada: Observational Infoveillance Study Using Social Media Time Series Data. Journal of Medical Internet Research 2021;23(8):e28716 View
  2. Wallinheimo A, Evans S. More Frequent Internet Use during the COVID-19 Pandemic Associates with Enhanced Quality of Life and Lower Depression Scores in Middle-Aged and Older Adults. Healthcare 2021;9(4):393 View
  3. Ding K, Yang J, Chin M, Sullivan L, Demirhan G, Violant-Holz V, Uvinha R, Dai J, Xu X, Popeska B, Mladenova Z, Khan W, Kuan G, Balasekaran G, Smith G. Mental Health among Adults during the COVID-19 Pandemic Lockdown: A Cross-Sectional Multi-Country Comparison. International Journal of Environmental Research and Public Health 2021;18(5):2686 View
  4. Sleigh J, Amann J, Schneider M, Vayena E. Qualitative analysis of visual risk communication on twitter during the Covid-19 pandemic. BMC Public Health 2021;21(1) View
  5. Adikari A, Nawaratne R, De Silva D, Ranasinghe S, Alahakoon O, Alahakoon D. Emotions of COVID-19: Content Analysis of Self-Reported Information Using Artificial Intelligence. Journal of Medical Internet Research 2021;23(4):e27341 View
  6. Mohamed Ridhwan K, Hargreaves C. Leveraging Twitter data to understand public sentiment for the COVID‐19 outbreak in Singapore. International Journal of Information Management Data Insights 2021;1(2):100021 View
  7. Kharlamov A, Raskhodchikov A, Pilgun M. Smart City Data Sensing during COVID-19: Public Reaction to Accelerating Digital Transformation. Sensors 2021;21(12):3965 View
  8. Viviani M, Crocamo C, Mazzola M, Bartoli F, Carrà G, Pasi G. Assessing vulnerability to psychological distress during the COVID-19 pandemic through the analysis of microblogging content. Future Generation Computer Systems 2021;125:446 View
  9. Chilman N, Morant N, Lloyd-Evans B, Wackett J, Johnson S. Twitter Users’ Views on Mental Health Crisis Resolution Team Care Compared With Stakeholder Interviews and Focus Groups: Qualitative Analysis. JMIR Mental Health 2021;8(6):e25742 View
  10. Ryan J, Sellak H, Brindal E. The Psychosocial Impacts of COVID-19 on a Sample of Australian Adults: Cross-sectional Survey and Sentiment Analysis. JMIR Public Health and Surveillance 2021;7(7):e29213 View
  11. Arpaci I, Alshehabi S, Mahariq I, Topcu A. An Evolutionary Clustering Analysis of Social Media Content and Global Infection Rates During the COVID-19 Pandemic. Journal of Information & Knowledge Management 2021;20(03):2150038 View
  12. Bathina K, ten Thij M, Valdez D, Rutter L, Bollen J, Osório F. Declining well-being during the COVID-19 pandemic reveals US social inequities. PLOS ONE 2021;16(7):e0254114 View
  13. Gianfredi V, Provenzano S, Santangelo O. What can internet users' behaviours reveal about the mental health impacts of the COVID-19 pandemic? A systematic review. Public Health 2021;198:44 View
  14. Marcantonio T, Valdez D, Jozkowski K. Assessing Young Adults’ Internal Feelings Related to Refusing Sexual Behavior. The Journal of Sex Research 2021;58(9):1184 View
  15. Maciaszek J, Lenart M, Misiak B, Grzebieluch J, Gawłowski P, Ciułkowicz M, Łuc D, Szcześniak D, Rymaszewska J. Unknown Enemy and Psychopathological Responses: A Cross-Sectional Nationwide Study Assessing the Knowledge About COVID-19. Frontiers in Psychiatry 2021;12 View
  16. Huang M, Khurana A, Mastorakos G, Wen A, He H, Wang L, Liu S, Wang Y, Zong N, Prigge J, Costello B, Shah N, Ting H, Fan J, Patten C, Liu H. Patient Portal Messaging for Asynchronous Virtual Care During the COVID-19 Pandemic: Retrospective Analysis. JMIR Human Factors 2022;9(2):e35187 View
  17. Hoefer G, Massachi T, Xu N, Nugent N, Huang J. Bridging the Social Distance: Offline to Online Social Support during the COVID-19 Pandemic. Proceedings of the ACM on Human-Computer Interaction 2022;6(CSCW2):1 View
  18. Edinger A, Valdez D, Walsh-Buhi E, Bollen J. Deep learning for topical trend discovery in online discourse about Pre-Exposure Prophylaxis (PrEP). AIDS and Behavior 2023;27(2):443 View
  19. Liew T, Lee C. Examining the Utility of Social Media in COVID-19 Vaccination: Unsupervised Learning of 672,133 Twitter Posts. JMIR Public Health and Surveillance 2021;7(11):e29789 View
  20. Burke M, Heft-Neal S, Li J, Driscoll A, Baylis P, Stigler M, Weill J, Burney J, Wen J, Childs M, Gould C. Exposures and behavioural responses to wildfire smoke. Nature Human Behaviour 2022;6(10):1351 View
  21. Huang C, Bandyopadhyay A, Fan W, Miller A, Gilbertson-White S, Chen Z. Mental toll on working women during the COVID-19 pandemic: An exploratory study using Reddit data. PLOS ONE 2023;18(1):e0280049 View
  22. Cuomo R, Purushothaman V, Calac A, McMann T, Li Z, Mackey T. Estimating County-Level Overdose Rates Using Opioid-Related Twitter Data: Interdisciplinary Infodemiology Study. JMIR Formative Research 2023;7:e42162 View
  23. Valdez D, Jozkowski K, Haus K, ten Thij M, Crawford B, Montenegro M, Lo W, Turner R, Bollen J. Assessing rigid modes of thinking in self-declared abortion ideology: natural language processing insights from an online pilot qualitative study on abortion attitudes. Pilot and Feasibility Studies 2022;8(1) View
  24. Zhang S, Liu M, Li Y, Chung J. Teens’ Social Media Engagement during the COVID-19 Pandemic: A Time Series Examination of Posting and Emotion on Reddit. International Journal of Environmental Research and Public Health 2021;18(19):10079 View
  25. Zhang S, Sun L, Zhang D, Li P, Liu Y, Anand A, Xie Z, Li D. The COVID-19 Pandemic and Mental Health Concerns on Twitter in the United States. Health Data Science 2022;2022 View
  26. Arias F, Zambrano Nunez M, Guerra-Adames A, Tejedor-Flores N, Vargas-Lombardo M. Sentiment Analysis of Public Social Media as a Tool for Health-Related Topics. IEEE Access 2022;10:74850 View
  27. Marchi V, Speak A, Ugolini F, Sanesi G, Carrus G, Salbitano F. Attitudes towards urban green during the COVID-19 pandemic via Twitter. Cities 2022;126:103707 View
  28. Fhon J, Püschel V, Cavalcante R, Cruz F, Gonçalves L, Li W, Silva A. Repercussões na saúde mental e infodemia de covid-19 de idosos paulistanos. Revista da Escola de Enfermagem da USP 2022;56 View
  29. Kim D, Park C, Kim E, Han J, Song H. Social Sharing of Emotion During the COVID-19 Pandemic. Cyberpsychology, Behavior, and Social Networking 2022;25(6):369 View
  30. Lieneck C, Bosworth M, Weaver E, Heinemann K, Patel J. Protective and Non-Protective Factors of Mental Health Distress in the United States during the COVID-19 Pandemic: A Systematic Review. Medicina 2021;57(12):1377 View
  31. Asghar M, Iqbal A, Seitamaa-Hakkarainen P, Barbera E. Breaching Learners’ Social Distancing through Social Media during the COVID-19 Pandemic. International Journal of Environmental Research and Public Health 2021;18(21):11012 View
  32. Valdez D, Unger J. Difficulty Regulating Social Media Content of Age-Restricted Products: Comparing JUUL’s Official Twitter Timeline and Social Media Content About JUUL. JMIR Infodemiology 2021;1(1):e29011 View
  33. Scarpino I, Zucco C, Vallelunga R, Luzza F, Cannataro M. Investigating Topic Modeling Techniques to Extract Meaningful Insights in Italian Long COVID Narration. BioTech 2022;11(3):41 View
  34. Winter R, Lavis A. The Impact of COVID-19 on Young People’s Mental Health in the UK: Key Insights from Social Media Using Online Ethnography. International Journal of Environmental Research and Public Health 2021;19(1):352 View
  35. Feng Y, Shah C. Unifying telescope and microscope: A multi-lens framework with open data for modeling emerging events. Information Processing & Management 2022;59(2):102811 View
  36. Lim S, Ng Q, Xin X, Lim Y, Boon E, Liew T. Public Discourse Surrounding Suicide during the COVID-19 Pandemic: An Unsupervised Machine Learning Analysis of Twitter Posts over a One-Year Period. International Journal of Environmental Research and Public Health 2022;19(21):13834 View
  37. İSMAİLOĞLU F. A Text Mining Analysis on Misinformation Regarding the COVID-19 Pandemic. Bilecik Şeyh Edebali Üniversitesi Fen Bilimleri Dergisi 2022;9(1):20 View
  38. Isch C, ten Thij M, Todd P, Bollen J. Quantifying changes in societal optimism from online sentiment. Behavior Research Methods 2022;55(1):176 View
  39. Bastani P, Hakimzadeh S, Bahrami M. Designing a conceptual framework for misinformation on social media: a qualitative study on COVID-19. BMC Research Notes 2021;14(1) View
  40. Mathayomchan B, Taecharungroj V, Wattanacharoensil W. Evolution of COVID-19 tweets about Southeast Asian Countries: topic modelling and sentiment analyses. Place Branding and Public Diplomacy 2023;19(3):317 View
  41. Valdez D, Goodson P. Neutral or Framed? A Sentiment Analysis of 2019 Abortion Laws. Sexuality Research and Social Policy 2022;19(3):936 View
  42. Russell A, Valdez D, Chiang S, Montemayor B, Barry A, Lin H, Massey P. Using Natural Language Processing to Explore “Dry January” Posts on Twitter: Longitudinal Infodemiology Study. Journal of Medical Internet Research 2022;24(11):e40160 View
  43. Culp F, Wu Y, Wu D, Ren Y, Raynor P, Hung P, Qiao S, Li X, Eichelberger K. Understanding Alcohol Use Discourse and Stigma Patterns in Perinatal Care on Twitter. Healthcare 2022;10(12):2375 View
  44. Ng R, Indran N, Liu L. Ageism on Twitter during the COVID‐19 pandemic. Journal of Social Issues 2022;78(4):842 View
  45. Han Y, Pan W, Li J, Zhang T, Zhang Q, Zhang E. Developmental Trend of Subjective Well-Being of Weibo Users During COVID-19: Online Text Analysis Based on Machine Learning Method. Frontiers in Psychology 2022;12 View
  46. Valdez D, Jozkowski K, Montenegro M, Crawford B, Jackson F. Identifying accurate pro‐choice and pro‐life identity labels in Spanish: Social media insights and implications for comparative survey research. Perspectives on Sexual and Reproductive Health 2022;54(4):166 View
  47. Golder S, Jefferson L, McHugh E, Essex H, Heathcote C, Castro Avila A, Dale V, Van Der Feltz‐Cornelis C, Bloor K. General practitioners' wellbeing during the COVID‐19 pandemic: Novel methods with social media data. Health Information & Libraries Journal 2023;40(4):400 View
  48. Gelashvili V, Martínez-Navalón J, Gómez-Borja M. Does the intensity of use of social media influence the economic sustainability of the university?. The Journal of Technology Transfer 2024;49(1):19 View
  49. Liu S, Liu J. Public attitudes toward COVID-19 vaccines on English-language Twitter: A sentiment analysis. Vaccine 2021;39(39):5499 View
  50. Tsao S, MacLean A, Chen H, Li L, Yang Y, Butt Z. Public Attitudes During the Second Lockdown: Sentiment and Topic Analyses Using Tweets From Ontario, Canada. International Journal of Public Health 2022;67 View
  51. Tušl M, Thelen A, Marcus K, Peters A, Shalaeva E, Scheckel B, Sykora M, Elayan S, Naslund J, Shankardass K, Mooney S, Fadda M, Gruebner O. Opportunities and challenges of using social media big data to assess mental health consequences of the COVID-19 crisis and future major events. Discover Mental Health 2022;2(1) View
  52. Fhon J, Püschel V, Cavalcante R, Cruz F, Gonçalves L, Li W, Silva A. Infodemic of covid-19 and repercussions on the mental health of the elderly from São Paulo. Revista da Escola de Enfermagem da USP 2022;56 View
  53. Volkert J, Taubner S, Berning A, Kling L, Wießner H, Georg A, Holl J. Transdiagnostic Mechanisms of Mental Health During the COVID-19 Pandemic on Adults and Families in Germany: Study Protocol of a Cross-Sectional and 1-Year Longitudinal Study. Frontiers in Psychology 2021;12 View
  54. Daimer S, Mihatsch L, Neufeld S, Murray G, Knolle F. Investigating the relationship of COVID-19 related stress and media consumption with schizotypy, depression, and anxiety in cross-sectional surveys repeated throughout the pandemic in Germany and the UK. eLife 2022;11 View
  55. Rezapour M, Elmshaeuser S, Vellido A. Artificial intelligence-based analytics for impacts of COVID-19 and online learning on college students’ mental health. PLOS ONE 2022;17(11):e0276767 View
  56. Chemnad K, Alshakhsi S, Almourad M, Altuwairiqi M, Phalp K, Ali R. Smartphone Usage before and during COVID-19: A Comparative Study Based on Objective Recording of Usage Data. Informatics 2022;9(4):98 View
  57. León-Sandoval E, Zareei M, Barbosa-Santillán L, Falcón Morales L, Pareja Lora A, Ochoa Ruiz G, Hošovský A. Monitoring the Emotional Response to the COVID-19 Pandemic Using Sentiment Analysis: A Case Study in Mexico. Computational Intelligence and Neuroscience 2022;2022:1 View
  58. Bahuguna A, Yadav D, Senapati A, Saha B, Pinto D, Beltrán B, Singh V. A unified deep neuro-fuzzy approach for COVID-19 twitter sentiment classification. Journal of Intelligent & Fuzzy Systems 2022;42(5):4587 View
  59. Levanti D, Monastero R, Zamani M, Eichstaedt J, Giorgi S, Schwartz H, Meliker J. Depression and Anxiety on Twitter During the COVID-19 Stay-At-Home Period in 7 Major U.S. Cities. AJPM Focus 2023;2(1):100062 View
  60. Ding Q, Massey D, Huang C, Grady C, Lu Y, Cohen A, Matzner P, Mahajan S, Caraballo C, Kumar N, Xue Y, Dreyer R, Roy B, Krumholz H. Tracking Self-reported Symptoms and Medical Conditions on Social Media During the COVID-19 Pandemic: Infodemiological Study. JMIR Public Health and Surveillance 2021;7(9):e29413 View
  61. Jones R, Mougouei D, Evans S. Understanding the emotional response to COVID‐19 information in news and social media: A mental health perspective. Human Behavior and Emerging Technologies 2021;3(5):832 View
  62. Chen R, Muralidharan K, Samelson‐Jones B. Digital haemophilia: Insights into the use of social media for haemophilia care, research and advocacy. Haemophilia 2022;28(2):247 View
  63. Lo Moro G, Scaioli G, Martella M, Pagani A, Colli G, Bert F, Siliquini R. Exploring Cyberaggression and Mental Health Consequences among Adults: An Italian Nationwide Cross-Sectional Study. International Journal of Environmental Research and Public Health 2023;20(4):3224 View
  64. León-Sandoval E, Zareei M, Barbosa-Santillán L, Falcón Morales L. Measuring the Impact of Language Models in Sentiment Analysis for Mexico’s COVID-19 Pandemic. Electronics 2022;11(16):2483 View
  65. Baird A, Xia Y, Cheng Y. Consumer perceptions of telehealth for mental health or substance abuse: a Twitter-based topic modeling analysis. JAMIA Open 2022;5(2) View
  66. Guazzini A, Gursesli M, Serritella E, Tani M, Duradoni M. Obsessive-Compulsive Disorder (OCD) Types and Social Media: Are Social Media Important and Impactful for OCD People?. European Journal of Investigation in Health, Psychology and Education 2022;12(8):1108 View
  67. Chiny M, Chihab M, Bencharef O, Chihab Y, Moumen A, Mejjad N, Slimani H. Analysis of sentiments conveyed through Twitter concerning COVID-19. SHS Web of Conferences 2021;119:07003 View
  68. Ntompras C, Drosatos G, Kaldoudi E. A high-resolution temporal and geospatial content analysis of Twitter posts related to the COVID-19 pandemic. Journal of Computational Social Science 2022;5(1):687 View
  69. Siriaraya P, Zhang Y, Kawai Y, Jeszenszky P, Jatowt A, Zhao J. A city-wide examination of fine-grained human emotions through social media analysis. PLOS ONE 2023;18(2):e0279749 View
  70. Sarangi A, Amor W, Co E, Javed S, Usmani S, Rashid A. Social Media Reinvented: Can Social Media Help Tackle the Post-Pandemic Mental Health Onslaught?. Cureus 2022 View
  71. Valdez D, Patterson M, Liu N. Computational analyses identify addiction help-seeking behaviors on the social networking website Reddit: Insights into online social interactions and addiction support communities. PLOS Digital Health 2022;1(11):e0000143 View
  72. Tang J, Arvind V, Dominy C, White C, Cho S, Kim J. How Are Patients Reviewing Spine Surgeons Online? A Sentiment Analysis of Physician Review Website Written Comments. Global Spine Journal 2023;13(8):2107 View
  73. Li M, Hua Y, Liao Y, Zhou L, Li X, Wang L, Yang J. Tracking the Impact of COVID-19 and Lockdown Policies on Public Mental Health Using Social Media: Infoveillance Study. Journal of Medical Internet Research 2022;24(10):e39676 View
  74. Göbel P, Sanlier N, Yilmaz S, Açikalin B, Kocabaş Ş. The Correlation between Social Media Addiction and Emotional Eating during the COVID-19 Quarantine Period. Ecology of Food and Nutrition 2023;62(1-2):60 View
  75. Rosenthal S, Tobin A. Self-esteem only goes so far: the moderating effect of social media screen time on self-esteem and depressive symptoms. Behaviour & Information Technology 2023;42(15):2688 View
  76. Bizzotto N, Morlino S, Schulz P. Misinformation in Italian Online Mental Health Communities During the COVID-19 Pandemic: Protocol for a Content Analysis Study. JMIR Research Protocols 2022;11(5):e35347 View
  77. Shi B, Xu K, Zhao J. The long-term impacts of air quality on fine-grained online emotional responses to haze pollution in 160 Chinese cities. Science of The Total Environment 2023;864:161160 View
  78. Drescher L, Roosen J, Aue K, Dressel K, Schär W, Götz A. The Spread of COVID-19 Crisis Communication by German Public Authorities and Experts on Twitter: Quantitative Content Analysis. JMIR Public Health and Surveillance 2021;7(12):e31834 View
  79. Wu D, Kasson E, Singh A, Ren Y, Kaiser N, Huang M, Cavazos-Rehg P. Topics and Sentiment Surrounding Vaping on Twitter and Reddit During the 2019 e-Cigarette and Vaping Use–Associated Lung Injury Outbreak: Comparative Study. Journal of Medical Internet Research 2022;24(12):e39460 View
  80. Li J, Pang P, Xiao Y, Wong D. Changes in Doctor–Patient Relationships in China during COVID-19: A Text Mining Analysis. International Journal of Environmental Research and Public Health 2022;19(20):13446 View
  81. Pickett A, Valdez D. Mining Online Discourse Related to Transgender Exclusive Policies in Interscholastic Sport: an Exploratory Natural Language Processing Study. Sexuality Research and Social Policy 2023;20(3):936 View
  82. Marshall C, Lanyi K, Green R, Wilkins G, Pearson F, Craig D. Using Natural Language Processing to Explore Mental Health Insights From UK Tweets During the COVID-19 Pandemic: Infodemiology Study. JMIR Infodemiology 2022;2(1):e32449 View
  83. Ren R, Yan B. Personal network protects, social media harms: Evidence from two surveys during the COVID-19 pandemic. Frontiers in Psychology 2022;13 View
  84. Abrams M, Pelullo A, Meisel Z, Merchant R, Purtle J, Agarwal A. State and Federal Legislators’ Responses on Social Media to the Mental Health and Burnout of Health Care Workers Throughout the COVID-19 Pandemic: Natural Language Processing and Sentiment Analysis. JMIR Infodemiology 2023;3:e38676 View
  85. Nguyen M, Burns C. The Psychological Benefits of COVID-19 Vaccination. Advances in Public Health 2021;2021:1 View
  86. Evans S, Jones R, Alkan E, Sichman J, Haque A, de Oliveira F, Mougouei D, Yan Z. The Emotional Impact of COVID-19 News Reporting: A Longitudinal Study Using Natural Language Processing. Human Behavior and Emerging Technologies 2023;2023:1 View
  87. Morita P, Zakir Hussain I, Kaur J, Lotto M, Butt Z. Tweeting for Health Using Real-time Mining and Artificial Intelligence–Based Analytics: Design and Development of a Big Data Ecosystem for Detecting and Analyzing Misinformation on Twitter. Journal of Medical Internet Research 2023;25:e44356 View
  88. Ye L, Chen Y, Cai Y, Kao Y, Wang Y, Chen M, Shia B, Qin L. Gender Differences in the Nonspecific and Health-Specific Use of Social Media Before and During the COVID-19 Pandemic: Trend Analysis Using HINTS 2017-2020 Data. Journal of Health Communication 2023;28(4):231 View
  89. Muitana G, Amato C. Topics, concerns, and feelings commented on Facebook after the first death by COVID-19 in Mozambique. Revista de Investigación e Innovación en Ciencias de la Salud 2023;5(1):press View
  90. Golos A, Guntuku S, Piltch-Loeb R, Leininger L, Simanek A, Kumar A, Albrecht S, Dowd J, Jones M, Buttenheim A, Taskin N. Dear Pandemic: A topic modeling analysis of COVID-19 information needs among readers of an online science communication campaign. PLOS ONE 2023;18(3):e0281773 View
  91. Dhelim S, Chen L, Das S, Ning H, Nugent C, Leavey G, Pesch D, Bantry-White E, Burns D. Detecting Mental Distresses Using Social Behavior Analysis in the Context of COVID-19: A Survey. ACM Computing Surveys 2023;55(14s):1 View
  92. Hosseini S, Camacho C, Donjuan K, Pego L, Escamilla J. Unplugging for Student Success: Examining the Benefits of Disconnecting from Technology during COVID-19 Education for Emergency Planning. Education Sciences 2023;13(5):446 View
  93. Laureate C, Buntine W, Linger H. A systematic review of the use of topic models for short text social media analysis. Artificial Intelligence Review 2023;56(12):14223 View
  94. Cho H, Li P, Ngien A, Tan M, Chen A, Nekmat E. The bright and dark sides of social media use during COVID-19 lockdown: Contrasting social media effects through social liability vs. social support. Computers in Human Behavior 2023;146:107795 View
  95. Watimin N, Zanuddin H, Rahamad M. Religious and racial tension breakout: an online pre-crisis detection strategy via sentiment analysis for riot crime prevention. Social Network Analysis and Mining 2023;13(1) View
  96. Rosado-Solomon E, Koopmann J, Lee W, Cronin M. Mental Health and Mental Illness in Organizations: A Review, Comparison, and Extension. Academy of Management Annals 2023;17(2):751 View
  97. Ramamoorthy T, Mappillairaju B. Tweet topics on cancer among Indian Twitter users—computational approach using latent Dirichlet allocation topic modelling. Journal of Computational Social Science 2023;6(2):1033 View
  98. Sun J, Lee S. “No more COVID-19 messages via social media, please”: the mediating role of COVID-19 message fatigue between information overload, message avoidance, and behavioral intention. Current Psychology 2023;42(24):20347 View
  99. Beierle F, Pryss R, Aizawa A. Sentiments about Mental Health on Twitter—Before and during the COVID-19 Pandemic. Healthcare 2023;11(21):2893 View
  100. Valdez D, Mena-Meléndez L, Crawford B, Arvind A, Jozkowski K. Online Social Media Reactions to the Overturn of Roe v. Wade: Public Health Implications and Policy Insights. Sexuality Research and Social Policy 2024;21(2):616 View
  101. Valdez D, Soto-Vásquez A, Montenegro M. Geospatial vaccine misinformation risk on social media: Online insights from an English/Spanish natural language processing (NLP) analysis of vaccine-related tweets. Social Science & Medicine 2023;339:116365 View
  102. Gao J, Gallegos G, West J. Public Health Policy, Political Ideology, and Public Emotion Related to COVID-19 in the U.S. International Journal of Environmental Research and Public Health 2023;20(21):6993 View
  103. Parker M, Valdez D, Rao V, Eddens K, Agley J. Results and Methodological Implications of the Digital Epidemiology of Prescription Drug References Among Twitter Users: Latent Dirichlet Allocation (LDA) Analyses. Journal of Medical Internet Research 2023;25:e48405 View
  104. Alamgir A, Ali Y, Khan S, Yousufzai A, Khan F. Prevalence of Anxiety associated with COVID-19 Pandemic among University Students of Karachi. Pakistan Journal of Health Sciences 2023:44 View
  105. Pendleton S. Exploring Stigma and Black Mental Health on Twitter. Journal of Health Communication 2023;28(7):425 View
  106. Zhou J, Sheppard-Law S, Xiao C, Smith J, Lamb A, Axisa C, Chen F. Leveraging twitter data to understand nurses’ emotion dynamics during the COVID-19 pandemic. Health Information Science and Systems 2023;11(1) View
  107. Chandrasekaran R, Bapat P, Venkata P, Moustakas E. Face time with physicians: How do patients assess providers in video-visits?. Heliyon 2023;9(6):e16883 View
  108. Lande J, Pillay A, Chandra R, Alam M. Deep learning for COVID-19 topic modelling via Twitter: Alpha, Delta and Omicron. PLOS ONE 2023;18(8):e0288681 View
  109. Alvarez-Mon M, Pereira-Sanchez V, Hooker E, Sanchez F, Alvarez-Mon M, Teo A. Content and User Engagement of Health-Related Behavior Tweets Posted by Mass Media Outlets From Spain and the United States Early in the COVID-19 Pandemic: Observational Infodemiology Study. JMIR Infodemiology 2023;3:e43685 View
  110. Wu Q, Street R. How communicative environments affect college students’ mental health help-seeking during COVID-19: a cross-sectional study. Journal of American College Health 2023:1 View
  111. Do R, Kim S, Lim Y, Kim S, Kwon H, Kim J, Lee S, Kim B. Korean adolescents’ coping strategies on self-harm, ADHD, insomnia during COVID-19: text mining of social media big data. Frontiers in Psychiatry 2023;14 View
  112. McMann T, Wenzel C, Le N, Li Z, Xu Q, Cuomo R, Mackey T. Detection and Characterization of Web-Based Pediatric COVID-19 Vaccine Discussions and Racial and Ethnic Minority Topics: Retrospective Analysis of Twitter Data. JMIR Pediatrics and Parenting 2023;6:e48004 View
  113. Kim A, Du J, Andrew D. Social media consumption and depressive symptoms during the COVID-19 lockdown: the mediating effect of physical activity. Frontiers in Psychiatry 2023;14 View
  114. Poole M, Pancer E, Philp M, Noseworthy T. COVID-19 and the decline of active social media engagement. European Journal of Marketing 2024;58(2):548 View
  115. Valdez D, Mena-Meléndez L, Crawford B, Jozkowski K. Analyzing Reddit Forums Specific to Abortion That Yield Diverse Dialogues Pertaining to Medical Information Seeking and Personal Worldviews: Data Mining and Natural Language Processing Comparative Study. Journal of Medical Internet Research 2024;26:e47408 View
  116. Esmaeilzadeh P. Privacy Concerns About Sharing General and Specific Health Information on Twitter: Quantitative Study. JMIR Formative Research 2024;8:e45573 View
  117. Tsironis G, Daglis T, Tsagarakis K. The 21 most practiced RE-s of circular economy from LinkedIn company profiles on a global scale. Resources, Conservation & Recycling Advances 2024;21:200202 View
  118. Battocchio A, Yang J, Dong C, Bertellotti E, Joo E, Teran C. “Do Good and Be ‘Liked’”: CSR Messages on Social Media during COVID-19 Pandemic and Consumer Responses. Journal of Current Issues & Research in Advertising 2024;45(2):219 View
  119. Wang S, Liang C, Gao Y, Ye Y, Qiu J, Tao C, Wang H. Social media insights into spatio-temporal emotional responses to COVID-19 crisis. Health & Place 2024;85:103174 View
  120. Heilemann M, Lai J, Cadiz M, Meza J, Flores Romero D, Wells K. Community Members’ Perceptions of a Resource-Rich Well-Being Website in California During the COVID-19 Pandemic: Qualitative Thematic Analysis. JMIR Formative Research 2024;8:e55517 View
  121. Wiciak M, Shazley O, Santhosh D. Social Media Behaviors and Lifestyle Changes in Young Adults (Ages 18-28 years) During the COVID-19 Pandemic: Analysis From an International Cross-Sectional Study. Journal of Primary Care & Community Health 2024;15 View
  122. Pérez Rave J, Zapata Jaramillo C, Jaramillo Álvarez G. Mental health in organizations from a healthcare analytics framework: taxonomic model, trends, and impact of COVID-19. Journal of Management Analytics 2024;11(1):62 View
  123. Yu D, Wing Y, Li T, Chan N. The Impact of Social Media Use on Sleep and Mental Health in Youth: a Scoping Review. Current Psychiatry Reports 2024;26(3):104 View
  124. Atilla F, Zwaan R. Impact of spatial distance on public attention and sentiment during the spread of COVID-19. Informatics in Medicine Unlocked 2024;45:101463 View
  125. Harris M, Levene M, Mudinas A. Time Series Analysis of Sentiment: A Comparison of the US and UK Coronavirus Subreddits. International Journal of Information Technology & Decision Making 2024;23(01):57 View
  126. Ramamoorthy T, Kulothungan V, Mappillairaju B. Topic modeling and social network analysis approach to explore diabetes discourse on Twitter in India. Frontiers in Artificial Intelligence 2024;7 View
  127. Fontenot H, Quist K, Glauberman G, Michel A, Zimet G. Impact of the COVID-19 pandemic on social media utilization, influences related to parental vaccine decision making, and opinions on trustworthy social media vaccination campaigns: A qualitative analysis. Human Vaccines & Immunotherapeutics 2024;20(1) View
  128. Rani S, Ahmed K, Subramani S. From Posts to Knowledge: Annotating a Pandemic-Era Reddit Dataset to Navigate Mental Health Narratives. Applied Sciences 2024;14(4):1547 View
  129. Ren S, Zhang M, Zhu C, Liu T, Zhang D. Decreased adaptability and increased social media use of Chinese female students during COVID-19: a multivariate latent growth curve model. Current Psychology 2024 View
  130. Rutter L, ten Thij M, Lorenzo-Luaces L, Valdez D, Bollen J, Henríquez P. Negative affect variability differs between anxiety and depression on social media. PLOS ONE 2024;19(2):e0272107 View
  131. Issaka B, Aidoo E, Wood S, Mohammed F. “Anxiety is not cute” analysis of twitter users’ discourses on romanticizing mental illness. BMC Psychiatry 2024;24(1) View
  132. Esquirol B, Prignano L, Díaz-Guilera A, Cozzo E. Analyzing user activity on Twitter during long-lasting crisis events: a case study of the Covid-19 crisis in Spain. Social Network Analysis and Mining 2024;14(1) View
  133. Pradeepa M, Kumaraperumal S, Kasat K, Phaneendra Maguluri L, Salma Shajahan U, Gaikwad S. Digital evolution: Investigating the dynamic interactions of learners with social media. Entertainment Computing 2024;50:100668 View
  134. Chepo M, Martin S, Déom N, Khalid A, Vindrola-Padros C. Twitter Analysis of Health Care Workers’ Sentiment and Discourse Regarding Post–COVID-19 Condition in Children and Young People: Mixed Methods Study. Journal of Medical Internet Research 2024;26:e50139 View
  135. Inuduka T, Yokose A, Managi S. Influencing cryptocurrency: analyzing celebrity sentiments on X (formerly Twitter) and their impact on bitcoin prices. Digital Finance 2024 View
  136. Lau N, Zhao X, O'Daffer A, Weissman H, Barton K. Pediatric Cancer Communication on Twitter: Natural Language Processing and Qualitative Content Analysis. JMIR Cancer 2024;10:e52061 View
  137. Linder A, Lusseau D. Resilience of human-nature interaction network to pandemic conditions. Science of The Total Environment 2024;931:172813 View
  138. Pan C, Wu Y, Wang S, Wang J, Chapman M, Zhang L, Li S. Pandemic fatigue? Insights from geotagged tweets on the spatiotemporal evolution of mental health in Canadian cities during COVID-19. Cities 2024;151:105100 View
  139. Bendau A, Petzold M, Ströhle A, Plag J. Viral Transmission? A Longitudinal Study of Media Use and Its Relation to Mental Strain During the First 2 Years of the COVID-19 Pandemic. International Journal of Behavioral Medicine 2024 View
  140. Sweeney C, Ennis E, Mulvenna M, Bond R, O'Neill S. Insights Derived From Text-Based Digital Media, in Relation to Mental Health and Suicide Prevention, Using Data Analysis and Machine Learning: Systematic Review. JMIR Mental Health 2024;11:e55747 View
  141. Ramamoorthy T, Kulothungan V, Mappillairaju B. Exploring stroke discourse on Twitter through content and network analysis among Indian users. Scientific Reports 2024;14(1) View
  142. Hamelin N, Rahimi R, Balaji S, Pismennaya I, Bui N, Ta H. Unveiling the power of video sentiment analysis for predicting advertising effectiveness: exploratory research on femvertising. Journal of Marketing Analytics 2024 View
  143. Golos A, Guntuku S, Buttenheim A. “Do not inject our babies”: a social listening analysis of public opinion about authorizing pediatric COVID-19 vaccines. Health Affairs Scholar 2024;2(7) View

Books/Policy Documents

  1. Singh A, Wu D. HCI International 2021 - Posters. View
  2. Shaikh S, Yayilgan S, Zoto E, Abomhara M. Intelligent Computing. View
  3. Dömök L, Fodor S. Perspectives in Business Informatics Research. View
  4. Salem O, Mehaoua A. Emerging Trends in Cybersecurity Applications. View
  5. Bollen J, ten Thij M, Lorenzo-Luaces L, Rutter L. Early Detection of Mental Health Disorders by Social Media Monitoring. View
  6. Sridevi M. Advances in Data Science and Analytics. View
  7. Juanals B, Minel J. Advances in Computational Collective Intelligence. View
  8. Martinis M, Scarpino I, Zucco C, Cannataro M. Computational Science – ICCS 2023. View
  9. Thakur N, Cho H, Cheng H, Lee H. HCI International 2023 – Late Breaking Papers. View
  10. Hoor-Ul-Ain S, Khan A, Siddiqui S, Dey I. Computational Methods in Psychiatry. View
  11. Maulana F, Adi P, Lestari D, Purnomo A, Wangean D. Proceedings of the 4th International Conference on Electronics, Biomedical Engineering, and Health Informatics. View
  12. Al-Khafaji A, Karan O. Emerging Trends and Applications in Artificial Intelligence. View
  13. Manikandan N, Thirunirai Senthil S. Advancements in Smart Computing and Information Security. View
  14. Kopel R, Fox C. Resilient Health. View