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1 Bo Pang, "Thumbs up?: sentiment classification using machine learning techniques" Association for Computational Linguistics 10 : 2002
2 Peter D. Turney, "Thumbs up or thumbs down?: semantic orientation applied to unsupervised classification of reviews" Association for Computational Linguistics 2002
3 Corinna Cortes, "Support vector networks" Kluwer Academic Publishers 20 : 273-297, 1995
4 M. Rahul, "Social Media Sentiment Analysis for Malayalam"
5 S. Sachin Kumar, "Sentiment analysis of tweets in malayalam using long short-term memory units and convolutional neural nets" Springer 2017
6 S. Soumya, "Sentiment analysis of malayalam tweets using different deep neural network models-case study" 2019
7 Deepu S. Nair, "Sentiment analysis of malayalam film review using machine learning techniques" 2015
8 Yequan Wang, "Sentiment analysis by capsules" 2018
9 Deepu S. Nair, "Sentima-sentiment extraction for malayalam" 2014
10 Tin Kam Ho, "Random decision forests" IEEE 1 : 1995
11 M. Anagha, "Fuzzy logic based hybrid approach for sentiment analysisl of malayalam movie reviews" 2015
12 M.P. Ashna, "Exicon based sentiment analysis system for malayalam language" 2017
13 Louise T. Su, "Evaluation measures for interactive information retrieval" 28 (28): 503-516, 1992
14 Neethu Mohandas, "Domain specific sentence level mood extraction from malayalam text" 2012
15 V. Kasthoori, "Computational Intelligence: Theories, Applications and Future Directions-Volume II" Springer 151-160, 2019
16 Daniel Jurafsky, "Classification: naive Bayes, logistic regression, sentiment" 2015
17 Ning Liu, "Attention-based sentiment reasoner for aspect-based sentiment analysis" 9 (9): 35-, 2019
18 P.K. Thulasi, "Aspect polarity recognition of movie and product reviews in Malayalam" 2016
19 Erik Cambria, "Affective computing and sentiment analysis" 31 (31): 102-107, 2016
20 Bernhard E. Boser, "A training algorithm for optimal margin classifiers" 1992
21 P. Jayan, "A subjective feature extraction for sentiment analysis in Malayalam language" 14 : 1-4, 2015