메뉴 건너뛰기




Volumn , Issue , 2016, Pages 17-25

After the boom no one tweets: Microblog-based influenza detection incorporating indirect information

Author keywords

Influenza surveillance; Location mention; Social network; Spatial analysis; Twitter

Indexed keywords

INFORMATION RETRIEVAL SYSTEMS; MONITORING;

EID: 85018262731     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/3007818.3007822     Document Type: Conference Paper
Times cited : (8)

References (42)
  • 2
    • 84855995176 scopus 로고    scopus 로고
    • Twitter earthquake detection: Earthquake monitoring in a social world
    • Earle PS, Bowden DC, Guy M. Twitter earthquake detection: earthquake monitoring in a social world. Ann Geophys -Italy. 2011;54(6):708-715. doi: 10.4401/ag-5364.
    • (2011) Ann GeophysItaly , vol.54 , Issue.6 , pp. 708-715
    • Earle, P.S.1    Bowden, D.C.2    Guy, M.3
  • 3
    • 77950541070 scopus 로고    scopus 로고
    • Earthquake twitter
    • Earle P. Earthquake Twitter. Nat Geosci. 2010;3(4):221-2. doi: 10.1038/ngeo832.
    • (2010) Nat Geosci. , vol.3 , Issue.4 , pp. 221-222
    • Earle, P.1
  • 4
    • 84922802451 scopus 로고    scopus 로고
    • Using twitter sentiment to forecast the 2013 Pakistani election and the 2014 Indian election
    • Kagan V, Stevens A, Subrahmanian VS. Using Twitter Sentiment to Forecast the 2013 Pakistani Election and the 2014 Indian Election. IEEE Intell. Syst. 2015;30(1):2-5.
    • (2015) IEEE Intell. Syst. , vol.30 , Issue.1 , pp. 2-5
    • Kagan, V.1    Stevens, A.2    Subrahmanian, V.S.3
  • 7
    • 84946594788 scopus 로고    scopus 로고
    • The effects of twitter sentiment on stock price returns
    • Ranco G, Aleksovski D, Caldarelli G, Grcar M, Mozetic I. The Effects of Twitter Sentiment on Stock Price Returns. PLoS One. 2015;10(9). doi: ARTN e013844110.1371/journal.pone.0138441.
    • (2015) PLoS One. , vol.10 , Issue.9
    • Ranco, G.1    Aleksovski, D.2    Caldarelli, G.3    Grcar, M.4    Mozetic, I.5
  • 8
    • 84929675571 scopus 로고    scopus 로고
    • Social media as a sensor of air quality and public response in China
    • Wang S, Paul MJ, Dredze M. Social media as a sensor of air quality and public response in China. Journal of Medical Internet research. 2015;17(3):e22. doi: 10.2196/jmir.3875.
    • (2015) Journal of Medical Internet Research. , vol.17 , Issue.3 , pp. e22
    • Wang, S.1    Paul, M.J.2    Dredze, M.3
  • 9
    • 84901906820 scopus 로고    scopus 로고
    • A largescale quantitative analysis of latent factors and sentiment in online doctor reviews
    • Wallace BC, Paul MJ, Sarkar U, Trikalinos TA, Dredze M. A largescale quantitative analysis of latent factors and sentiment in online doctor reviews. J Am Med Inform Assoc. 2014;21(6):1098-103. doi: 10.1136/amiajnl-2014-002711.
    • (2014) J Am Med Inform Assoc. , vol.21 , Issue.6 , pp. 1098-1103
    • Wallace, B.C.1    Paul, M.J.2    Sarkar, U.3    Trikalinos, T.A.4    Dredze, M.5
  • 11
    • 84855664643 scopus 로고    scopus 로고
    • Social and news media enable estimation of epidemiological patterns early in the 2010 Haitian cholera outbreak
    • Chunara R, Andrews JR, Brownstein JS. Social and news media enable estimation of epidemiological patterns early in the 2010 Haitian cholera outbreak. The American Journal of Tropical Medicine and Hygiene. 2012;86(1):39-45. doi: 10.4269/ajtmh.2012.11-0597.
    • (2012) The American Journal of Tropical Medicine and Hygiene. , vol.86 , Issue.1 , pp. 39-45
    • Chunara, R.1    Andrews, J.R.2    Brownstein, J.S.3
  • 14
    • 84937499054 scopus 로고    scopus 로고
    • Twitter improves influenza forecasting
    • Paul MJ, Dredze M, Broniatowski D. Twitter improves influenza forecasting. PLoS Curr. 2014; 6. doi: 10.1371/currents.outbreaks.90b9ed0f59bae4ccaa683a39865d9117.
    • (2014) PLoS Curr. , pp. 6
    • Paul, M.J.1    Dredze, M.2    Broniatowski, D.3
  • 15
    • 84891941337 scopus 로고    scopus 로고
    • National and local influenza surveillance through Twitter: An analysis of the 2012-2013 influenza epidemic
    • Broniatowski DA, Paul MJ, Dredze M. National and local influenza surveillance through Twitter: an analysis of the 2012-2013 influenza epidemic. PLoS One. 2013;8(12):e83672. doi: 10.1371/journal.pone.0083672.
    • (2013) PLoS One. , vol.8 , Issue.12 , pp. e83672
    • Broniatowski, D.A.1    Paul, M.J.2    Dredze, M.3
  • 16
    • 80053290412 scopus 로고    scopus 로고
    • Twitter catches the flu: Detecting influenza epidemics using Twitter
    • Aramaki E, Maskawa S, Morita M. Twitter catches the flu: detecting influenza epidemics using Twitter. EMNLP2011. pp. 1568-1576.
    • (2011) EMNLP , pp. 1568-1576
    • Aramaki, E.1    Maskawa, S.2    Morita, M.3
  • 20
    • 84907245332 scopus 로고    scopus 로고
    • Modeling the impact of Twitter on influenza epidemics
    • Pawelek KA, Oeldorf-Hirsch A, Rong L. Modeling the impact of Twitter on influenza epidemics. Math Biosci. Eng. 2014;11(6):1337-56. doi: 10.3934/mbe.2014.11.1337.
    • (2014) Math Biosci. Eng. , vol.11 , Issue.6 , pp. 1337-1356
    • Pawelek, K.A.1    Oeldorf-Hirsch, A.2    Rong, L.3
  • 21
    • 84910107444 scopus 로고    scopus 로고
    • A case study of the New York City 2012-2013 influenza season with daily geocoded Twitter data from temporal and spatiotemporal perspectives
    • Nagar R, Yuan Q, Freifeld CC, Santillana M, Nojima A, Chunara R et al. A case study of the New York City 2012-2013 influenza season with daily geocoded Twitter data from temporal and spatiotemporal perspectives. Journal of Medical Internet Research. 2014;16(10):e236. doi: 10.2196/jmir.3416.
    • (2014) Journal of Medical Internet Research. , vol.16 , Issue.10 , pp. e236
    • Nagar, R.1    Yuan, Q.2    Freifeld, C.C.3    Santillana, M.4    Nojima, A.5    Chunara, R.6
  • 22
    • 84891813761 scopus 로고    scopus 로고
    • Influenza-like illness surveillance on Twitter through automated learning of naive language
    • Gesualdo F, Stilo G, Agricola E, Gonfiantini MV, Pandolfi E, Velardi P et al. Influenza-like illness surveillance on Twitter through automated learning of naive language. PLoS One. 2013;8(12):e82489. doi: 10.1371/journal.pone.0082489.
    • (2013) PLoS One. , vol.8 , Issue.12 , pp. e82489
    • Gesualdo, F.1    Stilo, G.2    Agricola, E.3    Gonfiantini, M.V.4    Pandolfi, E.5    Velardi, P.6
  • 23
    • 84880826012 scopus 로고    scopus 로고
    • Use of hangeul Twitter to track and predict human influenza infection
    • Kim EK, Seok JH, Oh JS, Lee HW, Kim KH. Use of hangeul Twitter to track and predict human influenza infection. PLoS One. 2013;8(7):e69305. doi: 10.1371/journal.pone.0069305.
    • (2013) PLoS One. , vol.8 , Issue.7 , pp. e69305
    • Kim, E.K.1    Seok, J.H.2    Oh, J.S.3    Lee, H.W.4    Kim, K.H.5
  • 24
    • 79955757514 scopus 로고    scopus 로고
    • The use of twitter to track levels of disease activity and public concern in the U.S. during the influenza A H1N1 pandemic
    • Signorini A, Segre AM, Polgreen PM. The use of Twitter to track levels of disease activity and public concern in the U.S. during the influenza A H1N1 pandemic. PLoS One. 2011;6(5):e19467. doi: 10.1371/journal.pone.0019467.
    • (2011) PLoS One. , vol.6 , Issue.5 , pp. e19467
    • Signorini, A.1    Segre, A.M.2    Polgreen, P.M.3
  • 26
    • 84947256159 scopus 로고    scopus 로고
    • Using social media for actionable disease surveillance and outbreak management: A systematic literature review
    • Charles-Smith LE, Reynolds TL, Cameron MA, Conway M, Lau EHY, Olsen JM et al. Using Social Media for Actionable Disease Surveillance and Outbreak Management: A Systematic Literature Review. PLoS One. 2015;10(10). doi: ARTN e013970110.1371/journal.pone.0139701.
    • (2015) PLoS One , vol.10 , Issue.10
    • Charles-Smith, L.E.1    Reynolds, T.L.2    Cameron, M.A.3    Conway, M.4    Lau, E.H.Y.5    Olsen, J.M.6
  • 32
    • 84928567748 scopus 로고    scopus 로고
    • #Swineflu: Twitter predicts swine flu outbreak in 2009
    • Szomszor M, Kostkova P, Quincey Ed, editors. #Swineflu: Twitter Predicts Swine Flu Outbreak in 2009. eHealth 2010; 2009.
    • (2009) EHealth 2010
    • Szomszor, M.1    Kostkova, P.2    Quincey, Ed.3
  • 33
    • 84876796328 scopus 로고    scopus 로고
    • Geolocation prediction in social media data by finding location indicative words
    • Han B, Cook P, Baldwin T, editors. Geolocation prediction in social media data by finding location indicative words. COLING; 2012.
    • (2012) COLING
    • Han, B.1    Cook, P.2    Baldwin, T.3
  • 39
    • 84874240262 scopus 로고    scopus 로고
    • Nonlinear spread of rumor and inoculation strategies in the nodes with degree dependent tie strength in complex networks
    • Singh A, Singh YN. Nonlinear Spread of Rumor and Inoculation Strategies in the Nodes with Degree Dependent Tie Strength in Complex Networks. Acta Phys. Pol. B. 2013;44(1):5-28. doi: 10.5506/APhysPolB.44.5.
    • (2013) Acta Phys. Pol. B. , vol.44 , Issue.1 , pp. 5-28
    • Singh, A.1    Singh, Y.N.2
  • 40
    • 29344439866 scopus 로고    scopus 로고
    • The spread of a rumor or infection in a moving population
    • Kesten H, Sidoravicius V. The spread of a rumor or infection in a moving population. Ann Probab. 2005;33(6):2402-62. doi: 10.1214/009117905000000413.
    • (2005) Ann Probab. , vol.33 , Issue.6 , pp. 2402-2462
    • Kesten, H.1    Sidoravicius, V.2
  • 41
    • 84944254692 scopus 로고    scopus 로고
    • Combating rumor spread on social media: The effectiveness of refutation and warning
    • Ozturk P, Li HY, Sakamoto Y. Combating Rumor Spread on Social Media: The Effectiveness of Refutation and Warning. P Ann Hicss. 2015:2406-14. doi: 10.1109/Hicss.2015.288.
    • (2015) P Ann Hicss. , pp. 2406-2414
    • Ozturk, P.1    Li, H.Y.2    Sakamoto, Y.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.