{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,7,7]],"date-time":"2025-07-07T17:30:40Z","timestamp":1751909440483,"version":"3.41.0"},"publisher-location":"Republic and Canton of Geneva, Switzerland","reference-count":61,"publisher":"International World Wide Web Conferences Steering Committee","license":[{"start":{"date-parts":[[2017,4,3]],"date-time":"2017-04-03T00:00:00Z","timestamp":1491177600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"EU","award":["Cimplex Grant H2020 n.641191"],"award-info":[{"award-number":["Cimplex Grant H2020 n.641191"]}]},{"name":"NIH","award":["U54GM111274"],"award-info":[{"award-number":["U54GM111274"]}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2017,4,3]]},"DOI":"10.1145\/3038912.3052678","type":"proceedings-article","created":{"date-parts":[[2017,4,6]],"date-time":"2017-04-06T13:30:38Z","timestamp":1491485438000},"page":"311-319","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":49,"title":["Forecasting Seasonal Influenza Fusing Digital Indicators and a Mechanistic Disease Model"],"prefix":"10.1145","author":[{"given":"Qian","family":"Zhang","sequence":"first","affiliation":[{"name":"Northeastern University, Boston, MA, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Nicola","family":"Perra","sequence":"additional","affiliation":[{"name":"Northeastern University &amp; University of Greenwich, London, United Kingdom"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Daniela","family":"Perrotta","sequence":"additional","affiliation":[{"name":"ISI Foundation, Turin, Italy"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Michele","family":"Tizzoni","sequence":"additional","affiliation":[{"name":"ISI Foundation, Turin, Italy"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Daniela","family":"Paolotti","sequence":"additional","affiliation":[{"name":"ISI Foundation, Turin, Italy"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Alessandro","family":"Vespignani","sequence":"additional","affiliation":[{"name":"Northeastern University, Boston, MA, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2017,4,3]]},"reference":[{"key":"e_1_3_2_1_1_1","unstructured":"http:\/\/www.who.int\/mediacentre\/factsheets\/fs211\/en\/ March 2014."},{"key":"e_1_3_2_1_2_1","volume-title":"Medical care capacity for influenza outbreaks","author":"Glaser C.A.","year":"2002","unstructured":"C.A. Glaser and et al. Medical care capacity for influenza outbreaks, Los Angeles. Emerging infectious diseases, 8(6):569--574, 2002."},{"key":"e_1_3_2_1_3_1","volume-title":"Community influenza outbreaks and emergency department ambulance diversion. Annals of emergency medicine, 44(1):61--67","author":"Schull M.J.","year":"2004","unstructured":"M.J. Schull, M.M. Mamdani, and J. Fang. Community influenza outbreaks and emergency department ambulance diversion. Annals of emergency medicine, 44(1):61--67, 2004."},{"key":"e_1_3_2_1_4_1","volume-title":"Should we fear \"flu fear\" itself? Effects of H1N1 influenza fear on ED use. The American journal of emergency medicine, 30(2):275--282","author":"McDonnell W.M.","year":"2012","unstructured":"W.M. McDonnell, D.S. Nelson, and J.E. Schunk. Should we fear \"flu fear\" itself? Effects of H1N1 influenza fear on ED use. The American journal of emergency medicine, 30(2):275--282, 2012."},{"key":"e_1_3_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0094130"},{"key":"e_1_3_2_1_6_1","volume-title":"A systematic review of studies on forecasting the dynamics of influenza outbreaks. Influenza and other respiratory viruses, 8(3):309--316","author":"Nsoesie E.","year":"2014","unstructured":"E. Nsoesie, J. Brownstein, N. Ramakrishnan, and M. Marathe. A systematic review of studies on forecasting the dynamics of influenza outbreaks. Influenza and other respiratory viruses, 8(3):309--316, 2014."},{"key":"e_1_3_2_1_7_1","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pcbi.1002616"},{"key":"e_1_3_2_1_8_1","doi-asserted-by":"publisher","DOI":"10.1140\/epjds\/s13688-015-0054-0"},{"key":"e_1_3_2_1_9_1","doi-asserted-by":"publisher","DOI":"10.1145\/2487788.2488027"},{"key":"e_1_3_2_1_10_1","volume-title":"The parable of Google Flu: traps in big data analysis. Science, 343(14 March)","author":"Lazer D.","year":"2014","unstructured":"D. Lazer, R. Kennedy, G. King, and A. Vespignani. The parable of Google Flu: traps in big data analysis. Science, 343(14 March), 2014."},{"key":"e_1_3_2_1_11_1","doi-asserted-by":"publisher","DOI":"10.1073\/pnas.0906910106"},{"key":"e_1_3_2_1_12_1","doi-asserted-by":"publisher","DOI":"10.1186\/1741-7015-7-45"},{"key":"e_1_3_2_1_13_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jocs.2010.07.002"},{"key":"e_1_3_2_1_14_1","volume-title":"What can digital disease detection learn from (an external revision to) Google Flu Trends? American journal of preventive medicine, 47(3):341--347","author":"Santillana M.","year":"2014","unstructured":"M. Santillana, D.W. Zhang, B.M. Althouse, and J.W. Ayers. What can digital disease detection learn from (an external revision to) Google Flu Trends? American journal of preventive medicine, 47(3):341--347, 2014."},{"key":"e_1_3_2_1_15_1","doi-asserted-by":"publisher","DOI":"10.1186\/s12879-016-1669-x"},{"key":"e_1_3_2_1_16_1","volume-title":"Infectious Diseases of Humans: Dynamics and Control","author":"Anderson R.M.","year":"1992","unstructured":"R.M. Anderson and R.M. May. Infectious Diseases of Humans: Dynamics and Control. Oxford University Press, 1992."},{"key":"e_1_3_2_1_17_1","doi-asserted-by":"publisher","DOI":"10.1073\/pnas.0603181103"},{"key":"e_1_3_2_1_18_1","first-page":"37","volume-title":"Proceedings of the 2008 ACM\/IEEE conference on Supercomputing","author":"Barrett C.L.","unstructured":"C.L. Barrett and et al. Episimdemics: an efficient algorithm for simulating the spread of infectious disease over large realistic social networks. In Proceedings of the 2008 ACM\/IEEE conference on Supercomputing, page 37. IEEE Press, 2008."},{"key":"e_1_3_2_1_19_1","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pcbi.1000656"},{"key":"e_1_3_2_1_20_1","doi-asserted-by":"publisher","DOI":"10.1098\/rspb.2009.1605"},{"key":"e_1_3_2_1_21_1","doi-asserted-by":"publisher","DOI":"10.1038\/nature07634"},{"key":"e_1_3_2_1_22_1","doi-asserted-by":"publisher","DOI":"10.1145\/1964858.1964874"},{"key":"e_1_3_2_1_23_1","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0083672"},{"key":"e_1_3_2_1_24_1","doi-asserted-by":"publisher","DOI":"10.1109\/INFCOMW.2011.5928903"},{"key":"e_1_3_2_1_25_1","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pcbi.1004239"},{"key":"e_1_3_2_1_26_1","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pcbi.1003581"},{"key":"e_1_3_2_1_27_1","doi-asserted-by":"publisher","DOI":"10.1145\/2567948.2579272"},{"key":"e_1_3_2_1_28_1","doi-asserted-by":"publisher","DOI":"10.1137\/1.9781611973440.30"},{"key":"e_1_3_2_1_29_1","doi-asserted-by":"publisher","DOI":"10.1073\/pnas.1208772109"},{"key":"e_1_3_2_1_30_1","volume-title":"Nat. Comms","author":"Shaman J.","year":"2013","unstructured":"J. Shaman and et al. Real-time influenza forecasts during the 2012-2013 season. Nat. Comms, 4, Dec 2013."},{"key":"e_1_3_2_1_31_1","doi-asserted-by":"publisher","DOI":"10.1073\/pnas.1415012112"},{"key":"e_1_3_2_1_32_1","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pntd.0002713"},{"key":"e_1_3_2_1_33_1","volume-title":"Utilizing Nontraditional Data Sources for Near Real-Time Estimation of Transmission Dynamics During the 2015--2016 Colombian Zika Virus Disease Outbreak. JMIR public health and surveillance, 2(1):e30","author":"Majumder M.S.","year":"2016","unstructured":"M.S. Majumder and et al. Utilizing Nontraditional Data Sources for Near Real-Time Estimation of Transmission Dynamics During the 2015--2016 Colombian Zika Virus Disease Outbreak. JMIR public health and surveillance, 2(1):e30, 2016."},{"key":"e_1_3_2_1_34_1","unstructured":"http:\/\/ecdc.europa.eu\/en\/healthtopics\/influenza\/EISN\/Pages\/index.aspx Oct. 2016."},{"key":"e_1_3_2_1_35_1","unstructured":"http:\/\/ecdc.europa.eu\/en\/healthtopics\/influenza\/surveillance\/Pages\/influenza_case_definitions.aspx Oct. 2016."},{"key":"e_1_3_2_1_36_1","doi-asserted-by":"publisher","DOI":"10.1145\/1963192.1963301"},{"key":"e_1_3_2_1_37_1","unstructured":"Q. Samantha. Guide to the Twitter API Part 3 of 3: An Overview of Twitters Streaming API. http:\/\/blog.gnip.com\/tag\/gardenhose\/ January 2014."},{"key":"e_1_3_2_1_38_1","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0061981"},{"key":"e_1_3_2_1_39_1","volume-title":"January","author":"Accuracy GPS","year":"2014","unstructured":"GPS Accuracy. http:\/\/www.gps.gov\/systems\/gps\/performance\/accuracy\/, January 2014."},{"key":"e_1_3_2_1_40_1","doi-asserted-by":"publisher","DOI":"10.1109\/CIP.2010.5604088"},{"key":"e_1_3_2_1_41_1","first-page":"265","article-title":"You are what you tweet: Analyzing twitter for public health","volume":"20","author":"Paul M.J.","year":"2011","unstructured":"M.J. Paul and M. Dredze. You are what you tweet: Analyzing twitter for public health. ICWSM, 20:265--272, 2011.","journal-title":"ICWSM"},{"key":"e_1_3_2_1_42_1","first-page":"21","volume-title":"International Conference on Electronic Healthcare","author":"de Quincey E.","year":"2009","unstructured":"E. de Quincey and P. Kostkova. Early warning and outbreak detection using social networking websites: The potential of twitter. In International Conference on Electronic Healthcare, pages 21--24. Springer, 2009."},{"key":"e_1_3_2_1_43_1","first-page":"340","volume-title":"BIOCOMP","author":"Corley C.","year":"2009","unstructured":"C. Corley, A.R. Mikler, K.P. Singh, and D.J. Cook. Monitoring influenza trends through mining social media. In BIOCOMP, pages 340--346, 2009."},{"key":"e_1_3_2_1_44_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICPP.2010.66"},{"key":"e_1_3_2_1_45_1","doi-asserted-by":"publisher","DOI":"10.3390\/ijerph7020596"},{"key":"e_1_3_2_1_46_1","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0004378"},{"key":"e_1_3_2_1_47_1","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0019467"},{"key":"e_1_3_2_1_49_1","doi-asserted-by":"publisher","DOI":"10.1186\/1741-7015-10-165"},{"key":"e_1_3_2_1_50_1","doi-asserted-by":"publisher","DOI":"10.1016\/0025-5564(85)90064-1"},{"key":"e_1_3_2_1_51_1","doi-asserted-by":"publisher","DOI":"10.1080\/08898489209525336"},{"key":"e_1_3_2_1_52_1","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pmed.0040013"},{"key":"e_1_3_2_1_53_1","first-page":"63","volume-title":"Design and Analysis of Vaccine Studies","author":"Halloran M.E.","year":"2009","unstructured":"M.E. Halloran, I.M. Longini, and C.J. Struchiner. Binomial and Stochastic Transmission Models. In Design and Analysis of Vaccine Studies, pages 63--84. Springer Science Business Media, sep 2009."},{"key":"e_1_3_2_1_54_1","doi-asserted-by":"publisher","DOI":"10.1126\/science.1115717"},{"key":"e_1_3_2_1_55_1","doi-asserted-by":"publisher","DOI":"10.1126\/science.1176062"},{"key":"e_1_3_2_1_56_1","doi-asserted-by":"publisher","DOI":"10.1093\/aje\/kwm375"},{"key":"e_1_3_2_1_57_1","doi-asserted-by":"publisher","DOI":"10.1017\/S0950268807009144"},{"key":"e_1_3_2_1_58_1","volume-title":"Understanding the Demographics of Twitter Users. In ICWSM'11","author":"Mislove A.","year":"2011","unstructured":"A. Mislove, S. Lehmann, Y.Y. Ahn, J.P. Onnela, and J.N. Rosenquist. Understanding the Demographics of Twitter Users. In ICWSM'11, Barcelona, July 2011."},{"key":"e_1_3_2_1_59_1","volume-title":"November","author":"CDC. National Early Season Flu Vaccination Coverage","year":"2013","unstructured":"CDC. National Early Season Flu Vaccination Coverage, United States, November 2013."},{"key":"e_1_3_2_1_60_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-1-4612-1694-0_15"},{"key":"e_1_3_2_1_61_1","volume-title":"Estimating the secondary attack rate and serial interval of influenza-like illnesses using social media. Influenza and other respiratory viruses, 9(4):191--199","author":"Yom-Tov E.","year":"2015","unstructured":"E. Yom-Tov, I. Johansson-Cox, V. Lampos, and A. C. Hayward. Estimating the secondary attack rate and serial interval of influenza-like illnesses using social media. Influenza and other respiratory viruses, 9(4):191--199, 2015."},{"key":"e_1_3_2_1_62_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-23461-8_21"}],"event":{"name":"WWW '17: 26th International World Wide Web Conference","sponsor":["IW3C2 International World Wide Web Conference Committee","SIGWEB ACM Special Interest Group on Hypertext, Hypermedia, and Web"],"location":"Perth Australia","acronym":"WWW '17"},"container-title":["Proceedings of the 26th International Conference on World Wide Web"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3038912.3052678","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3038912.3052678","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,18]],"date-time":"2025-06-18T03:36:29Z","timestamp":1750217789000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3038912.3052678"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2017,4,3]]},"references-count":61,"alternative-id":["10.1145\/3038912.3052678","10.5555\/3038912"],"URL":"https:\/\/doi.org\/10.1145\/3038912.3052678","relation":{},"subject":[],"published":{"date-parts":[[2017,4,3]]},"assertion":[{"value":"2017-04-03","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}