Lexicon-based sentiment analysis in texts using Formal Concept Analysis

Formal concept analysis
Text mining
Authors

Manuel Ojeda Hernández

Domingo López-Rodríguez

Ángel Mora

Published

3 February 2023

Publication details

International Journal of Approximate Reasoning, vol. 155, pp 104-112

Links

DOI

 

Abstract

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.

Citation

Please, cite this work as:

[OLM23] M. Ojeda-Hernández, D. López-Rodríguez, and Á. Mora. “Lexicon-based sentiment analysis in texts using Formal Concept Analysis”. In: International Journal of Approximate Reasoning 155 (2023), pp. 104-112. ISSN: 0888-613X. DOI: https://doi.org/10.1016/j.ijar.2023.02.001. URL: https://www.sciencedirect.com/science/article/pii/S0888613X23000130.

@article{ijar2023,
    title = {Lexicon-based sentiment analysis in texts using Formal Concept Analysis},
    journal = {International Journal of Approximate Reasoning},
    volume = {155},
    pages = {104-112},
    year = {2023},
    issn = {0888-613X},
    doi = {https://doi.org/10.1016/j.ijar.2023.02.001},
    url = {https://www.sciencedirect.com/science/article/pii/S0888613X23000130},
    author = {Manuel Ojeda-Hernández and Domingo López-Rodríguez and Ángel Mora},
    keywords = {Formal Concept Analysis, Sentiment analysis, Polarity analysis, Text mining, Lexicon}
}

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Lexicon-based sentiment analysis in texts using Formal Concept Analysis

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  35. Lijun Zhang, Yuncheng Jiang (2023). Fusing semantic aspects for formal concept analysis using knowledge graphs. Multimedia Tools and Applications DOI
  36. Sunneng Sandino Berutu, Haeni Budiati, Jatmika Jatmika, et al. (2023). Data preprocessing approach for machine learning-based sentiment classification. JURNAL INFOTEL DOI