Memorias de investigación
Communications at congresses:
Applying Recurrent Neural Networks to Sentiment Analysis of Spanish Tweets
Year:2017

Research Areas
  • Artificial intelligence (neuronal nets, expert systems, etc)

Information
Abstract
This article presents the participation of the Intelligent Systems Group (GSI) at Universidad Polit ?ecnica de Madrid (UPM) in the Sentiment Analysis work- shop focused in Spanish tweets, TASS2017. We have worked on Task 1, aiming to classify sentiment polarity of Spanish tweets. For this task we propose a Recurrent Neural Network (RNN) architecture composed of Long Short-Term Memory (LSTM) cells followed by a feedforward network. The architecture makes use of two different types of features: word embeddings and sentiment lexicon values. The recurrent ar- chitecture allows us to process text sequences of different lengths, while the lexicon inserts directly into the system sentiment information. The results indicate that this feature combination leads to enhanced sentiment analysis performances.
International
No
Congress
TASS 2017: Workshop on Semantic Analysis at SEPLN
960
Place
Reviewers
Si
ISBN/ISSN
1613-0073
Start Date
20/09/2017
End Date
22/09/2017
From page
71
To page
76
Proceedings of TASS 2017: Workshop on Sentiment Analysis at SEPLN co-located with 33nd SEPLN Conference (SEPLN 2017)
Participants

Research Group, Departaments and Institutes related
  • Creador: Grupo de Investigación: Grupo de Sistemas Inteligentes
  • Departamento: Ingeniería de Sistemas Telemáticos