Empath: A Framework For Evaluating Entity-level Sentiment Analysis

dc.creatorWard C.B.
dc.creatorChoi Y.
dc.creatorSkiena S.
dc.creatorXavier E.C.
dc.date2011
dc.date2015-06-30T20:32:16Z
dc.date2015-11-26T14:50:54Z
dc.date2015-06-30T20:32:16Z
dc.date2015-11-26T14:50:54Z
dc.date.accessioned2018-03-28T22:02:18Z
dc.date.available2018-03-28T22:02:18Z
dc.identifier9781457715914
dc.identifier2011 8th International Conference And Expo On Emerging Technologies For A Smarter World, Cewit 2011. , v. , n. , p. - , 2011.
dc.identifier
dc.identifier10.1109/CEWIT.2011.6135866
dc.identifierhttp://www.scopus.com/inward/record.url?eid=2-s2.0-84857221210&partnerID=40&md5=29994161acfe2a4df2cd7f879695a855
dc.identifierhttp://www.repositorio.unicamp.br/handle/REPOSIP/108292
dc.identifierhttp://repositorio.unicamp.br/jspui/handle/REPOSIP/108292
dc.identifier2-s2.0-84857221210
dc.identifier.urihttp://repositorioslatinoamericanos.uchile.cl/handle/2250/1254311
dc.descriptionSentiment analysis is the fundamental component in text-driven monitoring or forecasting systems, where the general sentiment towards real-world entities (e.g., people, products, organizations) are analyzed based on the sentiment signals embedded in a myriad of web text available today. Building such systems involves several practically important problems, from data cleansing (e.g., boilerplate removal, web-spam detection), and sentiment analysis at individual mention-level (e.g., phrase, sentence-, document-level) to the aggregation of sentiment for each entity-level (e.g., person, company) analysis. Most previous research in sentiment analysis however, has focused only on individual mention-level analysis, and there has been relatively less work that copes with other practically important problems for enabling a large-scale sentiment monitoring system. In this paper, we propose Empath, a new framework for evaluating entity-level sentiment analysis. Empath leverages objective measurements of entities in various domains such as people, companies, countries, movies, and sports, to facilitate entity-level sentiment analysis and tracking. We demonstrate the utility of Empath for the evaluation of a large-scale sentiment system by applying it to various lexicons using Lydia, our own large scale text-analytics tool, over a corpus consisting of more than a terabyte of newspaper data. We expect that Empath will encourage research that encompasses end-to-end pipelines to enable a large-scale text-driven monitoring and forecasting systems. © 2011 IEEE.
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dc.languageen
dc.publisher
dc.relation2011 8th International Conference and Expo on Emerging Technologies for a Smarter World, CEWIT 2011
dc.rightsfechado
dc.sourceScopus
dc.titleEmpath: A Framework For Evaluating Entity-level Sentiment Analysis
dc.typeActas de congresos


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