Jonathan Juncal-Martínez

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This paper presents the approach of the GTI Research Group to SemEval-2015 task 10 on Sentiment Analysis in Twitter, or more specifically, subtasks A (Contextual Polarity Disambiguation) and B (Message Polarity Classification). We followed an unsupervised dependency parsing-based approach using a sentiment lexicon, created by means of an automatic polarity(More)
In recent years, the explosive growth of online media, such as blogs and social networking sites, has enabled individuals and organizations to write about their personal experiences and express opinions. Classifying these documents using a polarity metric is an arduous task. We propose a novel approach to predicting sentiment in online textual messages such(More)
This paper describes in detail the approach carried out by the GTI research group for SemEval 2016 Task 5: Aspect-Based Sentiment Analysis, for the different subtasks proposed, as well as languages and dataset contexts. In particular, we developed a system for category detection based on SVM. Then for the opinion target detection task we developed a system(More)
This paper presents the approach of the GTI Research Group to SemEval-2016 task 4 on Sentiment Analysis in Twitter, or more specifically, subtasks A (Message Polarity Classification), B (Tweet classification according to a two-point scale) and D (Tweet quantification according to a two-point scale). We followed a supervised approach based on the extraction(More)
This paper describes the participation of the GTI research group of AtlantTIC, University of Vigo, and Gradiant (Galician Research and Development Centre in Advanced Telecommunications), in the tass 2015 workshop. Both groups have worked together in the development of a hybrid approach for sentiment analysis, at a global level, of Twitter, proposed in task(More)
This paper describes the participation of the GTI research group of AtlantTIC, University of Vigo, in tass 2016. This workshop is framed within the XXXII edition of the Annual Congress of the Spanish Society for Natural Language Processing event. In this work we propose a supervised approach based on classifiers, for the aspect based sentiment analysis(More)
This paper presents an architecture developed in order to watch a movie in a cinema and follow subtitles in the mobile device. This architecture consists of a mobile application intended to display subtitles in an ordinary cinema, as well as a server containing the subtitles of those movies available at each cinema. The mobile device will connect to this(More)
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