Using SentiWordNet for multilingual sentiment analysis

By Kerstin Denecke. 2008 IEEE 24th International Conference on Data Engineering Workshop, 2008

416 citations recorded by the source corpus.

Subfields: Artificial Intelligence

View Paper: https://www.semanticscholar.org/paper/d51f037e575b3d7a54eaba0669fd5c2845da167b

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

1. C. Adline Sunitha
2. Ringki Das
3. Hanhoon Kang
4. Thoudam Doren Singh
5. Seong Joon Yoo
6. Amal Ganesh
7. Dongil Han
8. M. Devika

Citations in the corpus

• Sentiment Analysis: A Comparative Study on Different Approaches☆ (2016, methodology): “It is elaborated in [9], which explained a method, within multilingual framework to carry out the task of determining the polarity of the text.”
• Multimodal Sentiment Analysis: A Survey of Methods, Trends, and Challenges (2023, methodology): “[29] also introduced a text polarity prediction framework within a multilingual framework by leveraging SentiWordNet [30] lexical resource.”
• Senti-lexicon and improved Naïve Bayes algorithms for sentiment analysis of restaurant reviews (2012, background): “On the other hand, Courses and Surveys (2008), Chaumartin (2007), and Fahrni and Klenner (2008) used SentiWordNet.”