David Vilares

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We describe a system that classifies the polarity of Spanish tweets. We adopt a hybrid approach, which combines machine learning and linguistic knowledge acquired by means of NLP. We use part-of-speech tags, syntactic dependencies and semantic knowledge as features for a supervised classifier. Lexical particularities of the language used in Twitter are(More)
Millions of micro texts are published every day on Twitter. Identifying the sentiment present in them can be helpful for measuring the frame of mind of the public, their satisfaction with respect to a product or their support of a social event. In this context, polarity classification is a subfield of sentiment analysis focussed on determining whether the(More)
This paper describes our participation at RepLab 2014, a competitive evaluation for reputation monitoring on Twitter. The following tasks were addressed: (1) categorisation of tweets with respect to standard reputation dimensions and (2) characterisation of Twitter profiles, which includes: (2.1) identifying the type of those profiles, such as journalist or(More)
This work describes the system for the normalization of tweets in Spanish designed by the Language in the Information Society (LYS) Group of the University of A Coruña for Tweet-Norm 2013. It is a conceptually simple and flexible system, which uses few resources and that faces the problem from a lexical point of view. Buscando simplicidad y flexibilidad,(More)
This article describes an opinion mining system that classifies the polarity of Spanish texts. We propose a nlp-based approach which performs segmentation, tokenization and pos tagging of texts to then obtain the syntactic structure of sentences by means of a dependency parser. The syntactic structure is then used to address three of the most significant(More)
We introduce an approach to train lexical-ized parsers using bilingual corpora obtained by merging harmonized treebanks of different languages, producing parsers that can analyze sentences in either of the learned languages, or even sentences that mix both. We test the approach on the Universal Dependency Treebanks, training with MaltParser and(More)
This paper proposes an approach to solve message-and phrase-level polarity classification in Twitter, derived from an existing system designed for Spanish. As a first step, an ad-hoc preprocessing is performed. We then identify lexical, psychological and semantic features in order to capture different dimensions of the human language which are helpful to(More)
Twitter is an important platform for sharing opinions about politicians, parties and political decisions. These opinions can be exploited as a source of information to monitor the impact of politics on society. This article analyses the sentiment of 2,704,523 tweets referring to Spanish politicians and parties from a month in 2014-15. The article makes(More)