Yerai Doval

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This paper describes our participation at the third edition of the workshop on Sentiment Analysis focused on Spanish tweets, tass 2014. This year’s evaluation campaign includes four challenges: (1) global sentiment analysis, (2) topic classification, (3) aspect-extraction and (4) aspect-based sentiment analysis. Tasks 1 and 2 are addressed from a machine(More)
This paper describes the participation of the LyS group at tass 2015. In this year’s edition, we used a long short-term memory neural network to address the two proposed challenges: (1) sentiment analysis at a global level and (2) aspect-based sentiment analysis on football and political tweets. The performance of this deep learning approach is compared to(More)
We describe here our partipation in TweetLID. After having studied the problem of language identification, the resources available, and designed a text conflation approach for this kind of tasks, we joined the competition with two systems: the first one was based in the guesser langdetect, re-trained and adapted in order to work with conflated text; the(More)
In this article we describe the microtext normalization system we have used to participate in the Normalization of Noisy Text Task of the ACL W-NUT 2015 Workshop. Our normalization system was originally developed for text mining tasks on Spanish tweets. Our main goals during its development were flexibility, scalability and maintainability, in order to test(More)
This paper proposes an approach to solve messageand 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)
Personality recognition in source code constitutes a novel task in the field of author profiling on written text. In this paper we describe our proposal for the PR-SOCO shared task in FIRE 2016, which is based on a shallow recurrent LSTM neural network that tries to predict five personality traits of the author given a source code fragment. Our preliminary(More)
In this paper we describe our deep learning approach for solving both two-, threeand fiveclass tweet polarity classification, and twoand five-class quantification. We first trained a convolutional neural network using pretrained Twitter word embeddings, so that we could extract the hidden activation values from the hidden layers once some input had been fed(More)
In social media platforms special tokens abound such as hashtags and mentions in which multiple words are written together without spacing between them; e.g. #leapyear or @ryanreynoldsnet. Due to the way this kind of texts are written, this word assembly phenomenon can appear with its opposite, word segmentation, affecting any token of the text and making(More)
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