Senti-lexicon and improved Naïve Bayes algorithms for sentiment analysis of restaurant reviews
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SVM and Naïve Bayes are the key machine learning methods used for sentiment analysis in the literature.
“Support Vector Machine (SVM) and Naïve Bayes are the key machine learning methods used for sentiment analysis in the literature (Brob, 2013;Kang et al., 2012;Markopoulos et al., 2015;Shi & Li, 2011;Shimada et al., 2011;Ye et al., 2009), as they were conventionally designed for two-class classification problems.”
From Sentiment Analysis in Tourism: Capitalizing on Big Data (2019) · cites this paper as Kang et al., 2012
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Sentiment Analysis in Tourism: Capitalizing on Big Data
Alaei, A. R., Becken, S., & Stantic, B. (2019) · Journal of Travel Research · doi:10.1177/0047287517747753 · Cited by 622 · see citing works
Target-level sentiment analysis for news articles
Žitnik, S., Blagus, N., & Bajec, M. (2022) · Knowledge-Based Systems · doi:10.1016/j.knosys.2022.108939 · Cited by 32 · see citing works
- Authors
- Kang, H., Yoo, S. J., & Han, D.
- Affiliations
- Sejong University (KR)
- Corresponding author
- Yoo, Seong Joon
- Venue
- Expert Systems with Applications
- Publisher
- Elsevier BV
- Published
- 2012-04
- Volume
- 39
- Issue
- 5
- Pages
- 6000-6010
- ISSN
- 0957-4174 (ISSN-L)
- OpenAlex
- W2046858834
- Cited by
- 336
- References
- 0
- Citations by year
- 2026: 6 · 2025: 11 · 2024: 17 · 2023: 31 · 2022: 40 · 2021: 23 · 2020: 44 · 2019: 31 · 2018: 30 · 2017: 21 · 2016: 26 · 2015: 29 · 2014: 15 · 2013: 7 · 2012: 4
- FWCI
- 7.66
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Expert Systems with Applications (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Sentiment Analysis and Opinion Mining
- Physical Sciences › Computer Science › Artificial Intelligence › Text and Document Classification Technologies
- Physical Sciences › Computer Science › Artificial Intelligence › Topic Modeling
- Keywords
- sentiment analysis, restaurant reviews, sentiment lexicon, Naive Bayes classifier, class imbalance, unigram and bigram features, support vector machine, precision and recall
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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