Senti-lexicon and improved Naïve Bayes algorithms for sentiment analysis of restaurant reviews
By Hanhoon Kang, Seong Joon Yoo, Dongil Han. Expert systems with applications, 2012
397 citations recorded by the source corpus.
Subfields: Artificial Intelligence
View Paper: https://www.semanticscholar.org/paper/d19c4504b87338170e2da5084e3a75c76b418b22
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Artificial Intelligence
- Vadlamani Ravi
- Kumar Ravi
- Chaitanya Kulkarni
- Mayur Wankhade
- A. C. Rao
- Alireza Alaei
- Susanne Becken
- Bela Stantic
Citations in the corpus
- A survey on opinion mining and sentiment analysis: Tasks, approaches and applications (2015, background): “S# Tasks and applications #Articles References 1 Subjectivity Classification 6 [44], [75], [110], [163], [167], [174] 2 Polarity determination 43 [12], [26], [29], [32], [33], [35], [40], [45], [48], [50], [54], [57], [66], [85], [95], [96], [108], [109], [112], [114], [123], [126], [154], [156], [1”
- Approaches, Tools and Applications for Sentiment Analysis Implementation (2015, background): “An important study in this context is developed by [54] that provided a Senti-lexicon for restaurant reviews.”
- Hospitality and Tourism Online Reviews: Recent Trends and Future Directions (2015, background): “In order to improve accuracy, Kang, Yoo, and Han (2012) proposed an improved Naive Bayes algorithm for sentiment analysis.”
- Sentiment analysis algorithms and applications: A survey (2014, methodology): “com [32] 2011 TL Y Shared learning approach G Social Media, News data Blogspot, Flicker, youtube, CNN-BBC [33] 2012 FS N Statistical (HMM - LDA), ME Pos/Neg Movie Reviews N/A [34] 2012 BR Y Semantic G Restaurant Reviews N/A Spanish [35] 2012 SA Y Context-based method, NLP G Restaurant Reviews N/A [3”
- Ontology-based sentiment analysis of twitter posts (2013, neutral): “All rights reserved.”
- A survey on sentiment analysis methods, applications, and challenges (2022, methodology): “In the work of Kang et al. (2012) solved this problem using an improved version of the NB classifier.”
- Sentiment Analysis in Tourism: Capitalizing on Big Data (2019, methodology): “…(TF-IDF) (Shi & Li, 2011), stemmed word (Ganu et al., 2009), bag-ofwords (Markopoulos et al., 2015), information gain (IG) (Zheng & Ye, 2009), n-gram (Brob, 2013; Kang et al., 2012; Markopoulos et al., 2015; Zhang et al., 2011; Pablos et al., 2015) were proposed to characterise tourism reviews.”