Comparing the performance of knowledge-based and machine-learning approaches for the detection of emotions in an english Text

Barnes, Jeremy2015-10-092015-10-092015-10-09http://hdl.handle.net/10230/24828Treball de fi de màster en Lingüística Teòrica i AplicadaTutors: Juan María Garrido Almiñana i Antoni Badia i CardúsThe detection of emotion and sentiment analysis are very hot topics at the moment and the detection of emotion from written text still remains a difficult subject of this area of research. The main approaches to this task are knowledge-based approaches and machine-learning approaches. This paper examines the performance of two approaches (a knowledge-based and a machine-learning approach) on a small corpus of chat text annotated with emotion labels. It will be shown that the machine-learning approach used in this experiment outperforms the knowledge-based approach in all aspects.application/pdfengAttribution-NonCommercial-NoDerivs 3.0 SpainEnsenyament assistit per ordinadorLlenguatge i emocionsAdquisició del coneixement (Sistemes experts)Tractament del llenguatge natural (Informàtica)Comparing the performance of knowledge-based and machine-learning approaches for the detection of emotions in an english Textinfo:eu-repo/semantics/masterThesisinfo:eu-repo/semantics/openAccess