ej-sa-2017 at SemEval-2017 Task 4: Experiments for Target oriented Sentiment Analysis in Twitter

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dc.contributor.authorDovdon, Enkhzol
dc.contributor.authorSaias, José
dc.date.accessioned2017-09-11T11:33:01Z
dc.date.available2017-09-11T11:33:01Z
dc.date.issued2017-08-03
dc.description.abstractThis paper describes the system we have used for participating in Subtasks A (Message Polarity Classification) and B (Topic Based Message Polarity Classification according to a two-point scale) of SemEval2017 Task 4 Sentiment Analysis in Twitter. We used several features with a sentiment lexicon and NLP techniques, Maximum Entropy as a classifier for our system.por
dc.description.sponsorshipgLINK project of ”Erasmus Mundus Programme, Action 2 - STRAND 1, Lot 5, Asia (East)”por
dc.identifier.authoremailnd
dc.identifier.authoremailjsaias@uevora.pt
dc.identifier.citationE. Dovdon and J. Saias (2017). “ej-sa-2017 at semeval-2017 task 4: Experiments for target oriented sentiment analysis in twitter,” in Proceedings of the 11th International Workshop o n Semantic Evaluation (SemEval-2017), (Vancouver, Canada), pp. 635–638, Association for Computational Linguisticspor
dc.identifier.scientificarea283por
dc.identifier.urihttp://www.aclweb.org/anthology/S/S17/S17-2106.pdf
dc.identifier.urihttp://hdl.handle.net/10174/21321
dc.language.isoengpor
dc.peerreviewedyespor
dc.publisherACLpor
dc.rightsopenAccesspor
dc.subjectNLPpor
dc.subjectClassificationpor
dc.subjectOpinion Miningpor
dc.subjectSentiment Analysispor
dc.titleej-sa-2017 at SemEval-2017 Task 4: Experiments for Target oriented Sentiment Analysis in Twitterpor
dc.typearticlepor
degois.publication.firstPage635por
degois.publication.lastPage638por
degois.publication.locationVancouver, Canadapor
degois.publication.titleProceedings of the 11th International Workshop on Semantic Evaluation (SemEval-2017)por

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