Detecting trends on the Web: A multidisciplinary approach
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2014Metadata
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Dueñas Fernández, Rodrigo
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Detecting trends on the Web: A multidisciplinary approach
Abstract
This 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.
General note
Artículo de publicación ISI
Patrocinador
This 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: FBO16).
Identifier
URI: https://repositorio.uchile.cl/handle/2250/126705
DOI: DOI: 10.1016/j.inffus.2014.01.006
Quote Item
Information Fusion 20 (2014) 129–135
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