Journal
INTERNATIONAL JOURNAL OF APPROXIMATE REASONING
Volume 155, Issue -, Pages 104-112Publisher
ELSEVIER SCIENCE INC
DOI: 10.1016/j.ijar.2023.02.001
Keywords
Formal Concept Analysis; Sentiment analysis; Polarity analysis; Text mining; Lexicon
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In this paper, a novel approach for sentiment analysis using Formal Concept Analysis (FCA) to create customised dictionaries is presented. It outperforms other standard dictionaries by achieving better performance on a dataset of tweets categorised into positive and negative polarity.
In this paper, we present a novel approach for sentiment analysis that uses Formal Concept Analysis (FCA) to create dictionaries for classification. Unlike other methods that rely on pre-defined lexicons, our approach allows for the creation of customised dictionaries that are tailored to the specific data and tasks. By using a dataset of tweets categorised into positive and negative polarity, we show that our approach achieves a better performance than other standard dictionaries.(c) 2023 The Author(s). Published by Elsevier Inc. This is an open access article under the CC BY-NC-ND license (http://creativecommons .org /licenses /by-nc -nd /4 .0/).
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