| Vol-1896 urn:nbn:de:0074-1896-3 Copyright © 2017 for the individual papers by the papers' authors. Copying permitted for private and academic purposes. This volume is published and copyrighted by its editors.

# TASS 2017
Workshop on Sentiment Analysis at SEPLN

### Proceedings of TASS 2017: Workshop on Sentiment Analysis at SEPLN
co-located with 33nd SEPLN Conference (SEPLN 2017)

### Murcia, Spain, September 19th, 2017.

Edited by

### Julio Villena Román(1)
Miguel Á. García Cumbreras(2)
Eugenio Martínez Cámara(3)
Manuel C. Díaz Galiano(2)
Manuel García Vega(2)

(1)MeaningCloud, Madrid‬, Spain
(2)SINAI Research Group, Universidad de Jaén, Jaén, Spain
(3)Ubiquitous Knowledge Processing (UKP) Lab, Technische Universität Darmstadt, Darmstadt, Germany

## Table of Contents

- Preamble
- Committees
- Complete Proceedings

### Regular papers

- Overview of TASS 2017 13-21
  Eugenio Martínez Cámara, Manuel Carlos Díaz Galiano, Miguel Ángel García Cumbreras, Manuel García Vega
- A Genetic Programming Approach to Sentiment Analysis for Twitter: TASS'17 23-28
  Daniela Moctezuma, Mario Graff, Sabino Miranda-Jiménez, Eric S. Tellez, Abel Coronado, Claudia N. Sánchez, José Ortiz-Bejar
- ELiRF-UPV en TASS 2017: Análisis de Sentimientos en Twitter basado en Aprendizaje Profundo
  (ELiRF-UPV at TASS 2017: Sentiment Analysis in Twitter based on Deep Learning) 29-34
  Lluís-F. Hurtado, Ferran Pla, José-Ángel González
- Tecnolengua Lingmotif at TASS 2017: Spanish Twitter Dataset Classification Combining Wide-Coverage Lexical Resources and Text Features 35-42
  Antonio Moreno-Ortiz, Chantal Pérez Hernéndez
- OEG at TASS 2017: Spanish Sentiment Analysis of Tweets at Document Level 43-49-
  María Navas-Loro, Víctor Rodríguez-Doncel
- LexFAR en la competencia TASS 2017: Análisis de sentimientos en Twitter basado en lexicones
  (LexFAR at TASS 2017: Lexicon-based Sentiment Analysis in Twitter) 51-57
  José A. Reyes-Ortiz, Fabián Paniagua-Reyes, Belém Priego, Mireya Tovar
- Classifier Ensembles that Push the State-of-the-art in Sentiment Analysis of Spanish Tweets 59-64
  Jhon Adrián Cerón-Guzmán
- FastText como alternativa a la utilización de Deep Learning en corpus pequeños
  (FastText as an Alternative to using Deep Learning in Small Corpus) 65-69
  Rosa María Montañés Salas, Rafael del-Hoyo Alonso, Jorge Vea-Murguía Merck, Rocío Aznar Gimeno, Francisco José Lacueva-Pérez
- Applying Recurrent Neural Networks to Sentiment Analysis of Spanish Tweets 71-76
  Oscar Araque, Rodrigo Barbado, J. Fernando Sánchez-Rada, Carlos A. Iglesias
- RETUYT en TASS 2017: Análisis de Sentimiento de tweets en español utilizando SVM y CNN
  (RETUYT in TASS 2017: Sentiment Analysis for Spanish Tweets using SVM and CNN) 77-83
  Aiala Rosá, Luis Chiruzzo, Mathias Etcheverry, Santiago Castro
- C100TPUCP at TASS 2017: Word Embedding Experiments for Aspect-Based Sentiment Analysis in Spanish Tweets 85-90
  Franco Tume Fiestas, Marco A. Sobrevilla Cabezudo
- SINAI en TASS 2017: clasificación de la polaridad de tweets integrando información de usuario
  (SINAI in TASS 2017: Tweet Polarity Classification Integrating User Information) 91-96
  M. García-Vega, A. Montejo-Ráez, M. C. Díaz-Galiano, S. M. Jiménez-Zafra

2017-09-11: submitted by Eugenio Martínez Cámara, metadata incl. bibliographic data published under Creative Commons CC0
2017-09-12: published on CEUR-WS.org |valid HTML5|