Detecting trends on the web: a multidisciplinary approach

INFORMATION FUSION;
Inf. Fusion

dc.creatorDuenas-Fernandez, Rodrigo
dc.creatorVelasquez, Juan D.
dc.creatorL'Huillier, Gaston
dc.date2017-04-27T18:49:46Z
dc.date2022-07-07T01:40:58Z
dc.date2017-04-27T18:49:46Z
dc.date2022-07-07T01:40:58Z
dc.date2014
dc.date.accessioned2023-08-22T01:14:27Z
dc.date.available2023-08-22T01:14:27Z
dc.identifier1872-6305
dc.identifierD10I1198
dc.identifierD10I1198
dc.identifierWOS:000337863500013
dc.identifier1566-2535
dc.identifierhttps://hdl.handle.net/10533/196930
dc.identifier.urihttps://repositorioslatinoamericanos.uchile.cl/handle/2250/8304806
dc.descriptionThis paper introduces a framework for trend modeling and detection on the Web through the usage of Opinion Mining and Topic Modeling tools based on the fusion of freely available information. This framework consists of a four step model that runs periodically: crawl a set of predefined sources of documents; search for potential sources and extract topics from the retrieved documents; retrieve opinionated documents from social networks for each detected topic and extract sentiment information from them. The proposed framework was applied to a set of 20 sources of documents over a period of 8 months. After the analysis period and that the proposed experiments were run, an F-Measure of 0.56 was obtained for the detection of significant events, implying that the proposed framework is a feasible model of how trends could be represented through the analysis of documents freely available on the Web. (C) 2014 Elsevier B.V. All rights reserved.
dc.descriptionThis work was partially supported by FONDEF project D10I-1198, entitled WHALE: Web Hypermedia Analysis Latent Environment and the Millennium Institute on Complex Engineering Systems (ICM: P-05-004-F, CONICYT: FB016).
dc.description3
dc.descriptionFONDEF
dc.descriptionrduenas@ing.uchile.cl; jvelasqu@dii.uchile.cl; gaston@groupon.com
dc.descriptionFONDEF [D10I-1198]; WHALE: Web Hypermedia Analysis Latent Environment; Millennium Institute on Complex Engineering Systems [ICM: P-05-004-F, CONICYT: FB016]
dc.descriptionFONDEF
dc.languageENG
dc.publisherELSEVIER SCIENCE BV
dc.relationinstname: Conicyt
dc.relationreponame: Repositorio Digital RI2.0
dc.relationinstname: Conicyt
dc.relationreponame: Repositorio Digital RI2.0
dc.relationinfo:eu-repo/grantAgreement/Fondef/D10I1198
dc.relationinfo:eu-repo/semantics/dataset/hdl.handle.net/10533/93477
dc.relationhttps://doi.org/10.1016/j.inffus.2014.01.006
dc.rightsinfo:eu-repo/semantics/openAccess
dc.titleDetecting trends on the web: a multidisciplinary approach
dc.titleINFORMATION FUSION
dc.titleInf. Fusion
dc.typeArticulo
dc.typeinfo:eu-repo/semantics/article
dc.typeinfo:eu-repo/semantics/publishedVersion
dc.coverageAMSTERDAM


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