Multilingual sentiment analysis in social media

• Autores: Iñaki San Vicente Roncal
• Directores de la Tesis: Rodrigo Agerri Gascón (dir. tes.) , Germán Rigau Claramunt (dir. tes.)
• Lectura: En la Universidad del País Vasco - Euskal Herriko Unibertsitatea ( España ) en 2019
• Idioma: inglés
• Tribunal Calificador de la Tesis: Arantza Díaz de Ilarraza Sánchez (presid.) , Núria Bel Rafecas (secret.) , Horacio Rodríguez Hontoria (voc.)
• Enlaces
  • Tesis en acceso abierto en: ADDI
• Resumen

  • This thesis addresses the task of analysing sentiment in messages coming from social media. The ultimate goal was to develop a Sentiment Analysis system for Basque. However, because of the socio-linguistic reality of the Basque language a tool providing only analysis for Basque would not be enough for a real world application. Thus, we set out to develop a multilingual system, including Basque, English, French and Spanish.The thesis addresses the following challenges to build such a system:- Analysing methods for creating Sentiment lexicons, suitable for less resourced languages.- Analysis of social media (specifically Twitter): Tweets pose several challenges in order to understand and extract opinions from such messages. Language identification and microtext normalization are addressed.- Research the state of the art in polarity classification, and develop a supervised classifier that is tested against well known social media benchmarks.- Develop a social media monitor capable of analysing sentiment with respect to specific events, products or organizations.