awesome-sentiment-analysis/README.md

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# Sentment Analysis
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A curated list of Sentiment Analysis methods, implementations and misc.
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> Sentiment Analysis is the field of study that analyzes people's opinions, sentiments, evaluations, attitudes, and emotions from written languages. (Liu 2012)
## Survey Papers
Liu, Bing. "Sentiment analysis and opinion mining." Synthesis lectures on human language technologies 5.1 (2012): 1-167. [[pdf]](http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.244.9480&rep=rep1&type=pdf)
Vinodhini, G., and R. M. Chandrasekaran. "Sentiment analysis and opinion mining: a survey." International Journal 2.6 (2012): 282-292. [[pdf]](http://www.dmi.unict.it/~faro/tesi/sentiment_analysis/SA2.pdf)
Medhat, Walaa, Ahmed Hassan, and Hoda Korashy. "Sentiment analysis algorithms and applications: A survey." Ain Shams Engineering Journal 5.4 (2014): 1093-1113. [[pdf]](http://www.sciencedirect.com/science/article/pii/S2090447914000550)
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##
## Open Source Implementations
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### NodeJS
[thisandagain/sentiment]( https://github.com/thisandagain/sentiment): Lexical, Dictionary-based, AFINN-based.
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[thinkroth/Sentimental](https://github.com/thinkroth/Sentimental) Lexical, Dictionary-based, AFINN-based.
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### Java
[LingPipe](http://alias-i.com/): Lexical, Corpus-based.
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[CoreNLP](https://github.com/stanfordnlp/CoreNLP): Supervised Machine Learning
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### Python
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[nltk](http://www.nltk.org/): [VADER](https://github.com/cjhutto/vaderSentiment) sentiment analysis tool, Lexical, Dictionary-based, Rule-based. [[paper]](http://comp.social.gatech.edu/papers/icwsm14.vader.hutto.pdf)
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[vivekn/sentiment](https://github.com/vivekn/sentiment): Supervised Machine Learning, Naive Bayes Classifier. [[paper]](https://arxiv.org/abs/1305.6143)
[xiaohan2012/twitter-sent-dnn](https://github.com/xiaohan2012/twitter-sent-dnn): Supervised Machine Learning, Deep Learning, Convolutional Neural Network. [[paper]](http://nal.co/papers/Kalchbrenner_DCNN_ACL14)
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[kevincobain2000/sentiment_classifier](https://github.com/kevincobain2000/sentiment_classifier): Supervised Machine Learning, Naive Bayes Classifier, Max Entropy Classifier, SentiWordNet.
[pedrobalage/SemevalAspectBasedSentimentAnalysis](https://github.com/pedrobalage/SemevalAspectBasedSentimentAnalysis): Aspect-Based, Supervised Machine Learning, Conditional Random Field.
[ganeshjawahar/mem_absa](https://github.com/ganeshjawahar/mem_absa): Aspect-Based, Supervised Machine Learning, Deep Learning, Attention-based, External Memory. [[paper]](https://arxiv.org/abs/1605.08900)
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### R
[timjurka/sentiment](https://github.com/timjurka/sentiment): Supervised Machine Learning, Naive Bayes Classifier.
### Golang
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[cdipaolo/sentiment](https://github.com/cdipaolo/sentiment): Supervised Machine Learning, Naive Bayes Classifier. Based on [cdipaolo/goml](https://github.com/cdipaolo/goml).
### Ruby
[malavbhavsar/sentimentalizer](https://github.com/malavbhavsar/sentimentalizer): Lexical, Dictionary-based.
[7compass/sentimental](https://github.com/7compass/sentimental): Lexical, Dictionary-based.