Memorias de investigación
Communications at congresses:
Neural domain adaptation of sentiment lexicons
Year:2017

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

Information
Abstract
entiment lexicons are widely used in computational linguistics, as they represent a resource that directly contains subjective sentimental knowledge. Usually these sentiment lex- ica are generic and developed without any specific semantic domain in mind. Nonetheless, the domain context can be highly relevant for sentiment analysis, as it is known that word polarities can be influenced by domain-specific traits. This paper studies the problem of automatically generating domain- adapted sentiment lexicons that can be used in posterior senti- ment analysis tasks. We propose a neural network approach that modifies a sentiment lexicon using distantly annotated text of a certain domain. Additionally, we present a completely data-driven domain characterization metric that measures the centrality of a set of documents. Experimental work shows that this metric offers a measure of the generated lexicons? quality. Also, it is shown that the generated lexicons yield higher performance on domain-oriented sentiment analysis than a generic lexicon and other known baselines. Finally, it is also discussed that these extracted lexicons can be used for sentiment analysis even for approaches with no learning capabilities.
International
Si
Congress
2017 Seventh International Conference on Affective Computing and Intelligent Interaction Workshops and Demos (ACIIW)
960
Place
Reviewers
Si
ISBN/ISSN
978-1-5386-0680-3
10.1109/ACIIW.2017.8272598
Start Date
23/10/2017
End Date
26/10/2017
From page
105
To page
110
Affective Computing and Intelligent Interaction Workshops and Demos (ACIIW), 2017 Seventh International Conference on
Participants

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