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National and Local Influenza Surveillance through Twitter: An Analysis of the 2012-2013 Influenza Epidemic

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Cited by:

  1. Masafumi Ohashi & Akihiro Kameda & Osamu Kozan & Masahiro Kawasaki & Windy Iriana & Kenichi Tonokura & Daisuke Naito & Kayo Ueda, 2021. "Correlation of publication frequency of newspaper articles with environment and public health issues in fire-prone peatland regions of Riau in Sumatra, Indonesia," Palgrave Communications, Palgrave Macmillan, vol. 8(1), pages 1-10, December.
  2. Gianpaolo Zammarchi & Francesco Mola & Claudio Conversano, 2023. "Using sentiment analysis to evaluate the impact of the COVID-19 outbreak on Italy’s country reputation and stock market performance," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 32(3), pages 1001-1022, September.
  3. Paolo Brunori & Giuliano Resce, 2020. "Searching for the peak Google Trends and the Covid-19 outbreak in Italy," SERIES 04-2020, Dipartimento di Economia e Finanza - Università degli Studi di Bari "Aldo Moro", revised Apr 2020.
  4. Deepthi Kolady & Amrit Dumre & Weiwei Zhang & Kaiqun Fu & Marcia O'Leary & Laura Rose, 2023. "Social media use among American Indians in South Dakota: Preferences and perceptions," Papers 2307.01404, arXiv.org.
  5. Hyekyung Woo & Youngtae Cho & Eunyoung Shim & Kihwang Lee & Gilyoung Song, 2015. "Public Trauma after the Sewol Ferry Disaster: The Role of Social Media in Understanding the Public Mood," IJERPH, MDPI, vol. 12(9), pages 1-10, September.
  6. HeeChel Kim & Hong-Woo Chun & Seonho Kim & Byoung-Youl Coh & Oh-Jin Kwon & Yeong-Ho Moon, 2017. "Longitudinal Study-Based Dementia Prediction for Public Health," IJERPH, MDPI, vol. 14(9), pages 1-16, August.
  7. Ioannis Chalkiadakis & Hongxuan Yan & Gareth W Peters & Pavel V Shevchenko, 2021. "Infection rate models for COVID-19: Model risk and public health news sentiment exposure adjustments," PLOS ONE, Public Library of Science, vol. 16(6), pages 1-39, June.
  8. Fantazzini, Dean, 2020. "Short-term forecasting of the COVID-19 pandemic using Google Trends data: Evidence from 158 countries," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 59, pages 33-54.
  9. Cordova, Amado & Stanley, Karlyn D., 2021. "Public-private partnership for building a resilient broadband infrastructure in Puerto Rico," Telecommunications Policy, Elsevier, vol. 45(4).
  10. Jingwei Li & Choon-Ling Sia & Zhuo Chen & Wei Huang, 2021. "Enhancing Influenza Epidemics Forecasting Accuracy in China with Both Official and Unofficial Online News Articles, 2019–2020," IJERPH, MDPI, vol. 18(12), pages 1-13, June.
  11. Fernando Arias & Ariel Guerra-Adames & Maytee Zambrano & Efraín Quintero-Guerra & Nathalia Tejedor-Flores, 2022. "Analyzing Spanish-Language Public Sentiment in the Context of a Pandemic and Social Unrest: The Panama Case," IJERPH, MDPI, vol. 19(16), pages 1-19, August.
  12. Sequoia I Leuba & Reza Yaesoubi & Marina Antillon & Ted Cohen & Christoph Zimmer, 2020. "Tracking and predicting U.S. influenza activity with a real-time surveillance network," PLOS Computational Biology, Public Library of Science, vol. 16(11), pages 1-14, November.
  13. Tomeny, Theodore S. & Vargo, Christopher J. & El-Toukhy, Sherine, 2017. "Geographic and demographic correlates of autism-related anti-vaccine beliefs on Twitter, 2009-15," Social Science & Medicine, Elsevier, vol. 191(C), pages 168-175.
  14. Samuel V Scarpino & James G Scott & Rosalind M Eggo & Bruce Clements & Nedialko B Dimitrov & Lauren Ancel Meyers, 2020. "Socioeconomic bias in influenza surveillance," PLOS Computational Biology, Public Library of Science, vol. 16(7), pages 1-19, July.
  15. Ira Puspitasari & Alia Firdauzy, 2019. "Characterizing Consumer Behavior in Leveraging Social Media for E-Patient and Health-Related Activities," IJERPH, MDPI, vol. 16(18), pages 1-17, September.
  16. Logan C Brooks & David C Farrow & Sangwon Hyun & Ryan J Tibshirani & Roni Rosenfeld, 2018. "Nonmechanistic forecasts of seasonal influenza with iterative one-week-ahead distributions," PLOS Computational Biology, Public Library of Science, vol. 14(6), pages 1-29, June.
  17. Hongying Dai & Brian R. Lee & Jianqiang Hao, 2017. "Predicting Asthma Prevalence by Linking Social Media Data and Traditional Surveys," The ANNALS of the American Academy of Political and Social Science, , vol. 669(1), pages 75-92, January.
  18. Amir Hassan Zadeh & Hamed M. Zolbanin & Ramesh Sharda & Dursun Delen, 2019. "Social Media for Nowcasting Flu Activity: Spatio-Temporal Big Data Analysis," Information Systems Frontiers, Springer, vol. 21(4), pages 743-760, August.
  19. Zeynep Ertem & Dorrie Raymond & Lauren Ancel Meyers, 2018. "Optimal multi-source forecasting of seasonal influenza," PLOS Computational Biology, Public Library of Science, vol. 14(9), pages 1-16, September.
  20. Jose L Herrera & Ravi Srinivasan & John S Brownstein & Alison P Galvani & Lauren Ancel Meyers, 2016. "Disease Surveillance on Complex Social Networks," PLOS Computational Biology, Public Library of Science, vol. 12(7), pages 1-16, July.
  21. Ibrahim Musa & Hyun Woo Park & Lkhagvadorj Munkhdalai & Keun Ho Ryu, 2018. "Global Research on Syndromic Surveillance from 1993 to 2017: Bibliometric Analysis and Visualization," Sustainability, MDPI, vol. 10(10), pages 1-20, September.
  22. David A. Broniatowski, 2018. "Building the tower without climbing it: Progress in engineering systems," Systems Engineering, John Wiley & Sons, vol. 21(3), pages 259-281, May.
  23. David A. Broniatowski & Conrad Tucker, 2017. "Assessing causal claims about complex engineered systems with quantitative data: internal, external, and construct validity," Systems Engineering, John Wiley & Sons, vol. 20(6), pages 483-496, November.
  24. Muhammad Imran & Umair Qazi & Ferda Ofli, 2022. "TBCOV: Two Billion Multilingual COVID-19 Tweets with Sentiment, Entity, Geo, and Gender Labels," Data, MDPI, vol. 7(1), pages 1-27, January.
  25. Svitlana Volkova & Ellyn Ayton & Katherine Porterfield & Courtney D Corley, 2017. "Forecasting influenza-like illness dynamics for military populations using neural networks and social media," PLOS ONE, Public Library of Science, vol. 12(12), pages 1-22, December.
  26. Valentina Lorenzoni & Gianni Andreozzi & Andrea Bazzani & Virginia Casigliani & Salvatore Pirri & Lara Tavoschi & Giuseppe Turchetti, 2022. "How Italy Tweeted about COVID-19: Detecting Reactions to the Pandemic from Social Media," IJERPH, MDPI, vol. 19(13), pages 1-14, June.
  27. Yufang Wang & Kuai Xu & Yun Kang & Haiyan Wang & Feng Wang & Adrian Avram, 2020. "Regional Influenza Prediction with Sampling Twitter Data and PDE Model," IJERPH, MDPI, vol. 17(3), pages 1-12, January.
  28. Xiaodong Cao & Piers MacNaughton & Zhengyi Deng & Jie Yin & Xi Zhang & Joseph G. Allen, 2018. "Using Twitter to Better Understand the Spatiotemporal Patterns of Public Sentiment: A Case Study in Massachusetts, USA," IJERPH, MDPI, vol. 15(2), pages 1-15, February.
  29. Qiong Jia & Yue Guo & Guanlin Wang & Stuart J. Barnes, 2020. "Big Data Analytics in the Fight against Major Public Health Incidents (Including COVID-19): A Conceptual Framework," IJERPH, MDPI, vol. 17(17), pages 1-21, August.
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