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

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 extra...

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Bibliographic Details
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
Description
Summary: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.

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