Open AccessIrony Sentence Detection Techniques Using Fuzzy Historical Classifier
Author(s) -
Adhitia Erfina,
Yeffry Handoko Putra
Publication year - 2019
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/662/6/062004
Subject(s) - irony , utterance , sentence , linguistics , value (mathematics) , classifier (uml) , psychology , meaning (existential) , fuzzy logic , natural language processing , computer science , artificial intelligence , philosophy , machine learning , psychotherapist
The purpose of this study is to presents a new approach to the extraction of the meaning of sentences that are irony, that is by way of classifying someone based on their utterances in the past. The history of one’s utterances influences the assessment of a sentence having an irony tendency or not, for example when someone often speaks negatively, suddenly gives positive opinion on a topic while other people give negative opinions on the topic. The fuzzy logic method needs to be used to assess the historical tendency of one’s utterances when the values of positive and negative sentiments are almost balanced so that the value of the majority of sentiments is unclear. The results show that the greater the level of difference in sentiment between a topic and the higher the level of the historical tendency of a person’s utterance, the higher the value of the potential irony of the utterance.