Toward a unifying model for Opinion, Sentiment and Emotion information extraction

• Main Authors: Fraisse, Amel, Paroubek, Patrick
• Other Authors: Laboratoire d'Informatique pour la Mécanique et les Sciences de l'Ingénieur (LIMSI), Université Paris-Sud - Paris 11 (UP11)-Sorbonne Université - UFR d'Ingénierie (UFR 919), Sorbonne Université (SU)-Sorbonne Université (SU)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Université Paris Saclay (COmUE)
• Format: Conference Object
• Language: English
• Published: HAL CCSD 2014
• Subjects: Affective Lexicons; Sentiment Analysis; Opinion mining; Affective Lexicon; [INFO.INFO-TT]Computer Science [cs]/Document and Text Processing; Iceland
• Online Access: https://hal.science/hal-01613403; https://hal.science/hal-01613403/document; https://hal.science/hal-01613403/file/amel_fraisse.pdf

International audience This paper presents a logical formalization of a set 20 semantic categories related to opinion, emotion and sentiment. Our formalization is based on the BDI model (Belief, Desire and Intetion) and constitues a first step toward a unifying model for subjective information extraction. The separability of the subjective classes that we propose was assessed both formally and on two subjective reference corpora.