AORESCUanálisis de Opinión en Redes Sociales y Contenidos Generados por Usuarios

  1. José A. Troyano Jiménez
  2. L. Alfonso Ureña López
  3. Manuel J. Maña López
  4. Fermín Cruz Mata
  5. Fernando Enríquez de Salamanca Ros
Journal:
Procesamiento del lenguaje natural

ISSN: 1135-5948

Year of publication: 2015

Issue: 55

Pages: 153-156

Type: Article

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Abstract

AORESCU project main goals are focused on the retrieval and processing of information generated by users about an entity. The idea is to get insights from this information that help us to understand the perception of users about an entity. We can retrieve two types of information from web 2.0 sources: structured information (e.g. numerical rating) and unstructured (mainly in the form of texts in natural language). The techniques and tools used in the project are adaptable to any domain. We chose the tourism sector as application domain since it is a sector with an important economic activity and because it is easy to find user generated content about touristic resources. The project has four main phases: the retrieval of information from different sources about the entities (for the tourism sector, these entities are hotels, restaurants, natural spaces, monuments,...), the definition of a data model to represent this information, the development of text analysis tools to process user comments and the development of a web application to query and analyze the processed data.

Bibliographic References

  • Cotelo, J.M., Cruz, F.L. Troyano, J.A. 2014. Dynamic topic-related tweet retrieval. JASIST. 65(3): 513-523
  • Cruz Díaz, N.P., Taboada, Mitkov, R. 2015. A Machine Learning Approach to Negation and Speculation Detection for Sentiment Analysis. JASIST. Pendiente de publicación.
  • Cruz, F.L., Troyano, J.A., Enríquez, F., Ortega, F.J., Vallejo, C.G. 2013. 'Long autonomy or long delay?' The importance of domain in opinion mining. Expert Systems with Applications. 40(8): 3174-3184.
  • Cruz, F.L., Troyano, B., Pontes, F., Ortega, F.J. 2014. Building layered, multilingual sentiment lexicons at synset and lemma levels. Expert Systems with Applications. 41(13): 5984–5994.
  • Molina-González, M. Dolores, Martínez-Cámara, Eugenio, Martín-Valdivia, M. Teresa, Perea-Ortega, Jose M. 2013. Semantic Orientation for Polarity Classification in Spanish Reviews. Expert Systems with Applications. 40(18):7250- 7257.
  • Montejo-Ráez, Arturo, Martínez-Cámara, Eugenio, Martín-Valdivia, M. Teresa, Ureña-López, L. Alfonso. 2014. A Knowledge-Based Approach for Polarity Classification in Twitter. JASIST. 65(2):414-425.
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