%0 Book Section
%@nexthigherunit 8JMKD3MGPCW/43SRC6S
%@holdercode {isadg {BR SPINPE} ibi 8JMKD3MGPCW/3DT298S}
%@resumeid
%@resumeid
%@resumeid
%@resumeid 8JMKD3MGP5W/3C9JHUB
%X In Brazil, the summer season is the wettest period in which many disasters can happen, such as landslides and floods. In recent years, even with the rainy season, the metropolitan region of São Paulo (Brazil) suffers a severe water crisis. Given this scenario, monitoring of rainfall is fundamental for taking preventive actions and planning in the various business branches. Thus, the use of computers to develop tools that assist the rainfall monitoring can help extend the coverage of the existing solutions. Moreover, it is known that, every day, the number of social media users is increasing, and consequently increases the amount of content published in these medias. The objective of this study is to analyze the contents of the Twitter social media, especially the tweets related to rainfall events in order to determine whether this information can contribute to the monitoring of rainfall events in Brazil. More than 1 million tweets published in Brazil related to rainfall were collected in a period of 30 days. Gathered tweets were analyzed and evaluated taking into account the data collected by automatic weather stations (AWS or EMA). The results were satisfactory and indicate a relationship between the geolocated tweets and data from AWS.
%@mirrorrepository urlib.net/www/2011/03.29.20.55
%E Lafiti, Shahram,
%T Using Tweets for Rainfall Monitoring
%@isbn 9783319324661
%S Advances in Intelligent Systems and Computing
%@electronicmailaddress luiz.guarino@cptec.inpe.br
%@electronicmailaddress
%@electronicmailaddress mario.figueiredo@inpe.br
%@electronicmailaddress nelson.ferreira@inpe.br
%@secondarytype PRE LI
%K Twitter, Hashtags, Geolocation, Social media analysis.
%@usergroup lattes
%@usergroup self-uploading-INPE-MCTI-GOV-BR
%B Advances in Intelligent Systems and Computing
%@group DSA-CPT-INPE-MCTI-GOV-BR
%@group
%@group DSA-CPT-INPE-MCTI-GOV-BR
%@group DSA-CPT-INPE-MCTI-GOV-BR
%@tertiarymark Trabalho não Vinculado à Tese/Dissertação
%F lattes: 8626122636195184 5 VasconcelosSanNetFerVas:2016:UsTwRa
%U http://link.springer.com/10.1007/978-3-319-32467-8_100
%2 sid.inpe.br/plutao/2016/06.13.19.25.01
%@affiliation Instituto Nacional de Pesquisas Espaciais (INPE)
%@affiliation
%@affiliation Instituto Nacional de Pesquisas Espaciais (INPE)
%@affiliation Instituto Nacional de Pesquisas Espaciais (INPE)
%@versiontype finaldraft
%I Springer International Publishing
%P 1157-1167
%4 sid.inpe.br/plutao/2016/06.13.19.25
%@documentstage not transferred
%D 2016
%V 448
%@doi 10.1007/978-3-319-32467-8_100
%O International Conference on Information Technology, 13
%A Vasconcelos, Luiz Eduardo Guarino de,
%A Santos, Eder C. M.,
%A Figueiredo Neto, Mário Lemes de,
%A Ferreira, Nelson Jesus,
%@area MET