sentiment analysis resources combined

sentiment analysis_full

Supervised - Machine learning based
Unsupervised - Lexicon based

English lang:
  http://www.cs.uic.edu/~liub/FBS/sentiment-analysis.html#lexicon
  http://www.cs.uic.edu/~liub/FBS/opinion-lexicon-English.rar - lexicon sentiment dictionary
  http://www.cs.uic.edu/~liub/FBS/opinion-lexicon-English.rar
  https://sites.google.com/site/datascienceslab/projects/multilingualsentiment
  http://stackoverflow.com/questions/4188706/sentiment-analysis-dictionaries?rq=1
  http://stackoverflow.com/questions/3920759/unsupervised-sentiment-analysis
  http://stackoverflow.com/questions/4199441/best-algorithmic-approach-to-sentiment-analysis - Best approach
  http://streamhacker.com/2010/05/10/text-classification-sentiment-analysis-naive-bayes-classifier/ - Opensource NLTK
  
Emtion sentiments
  http://saifmohammad.com/WebPages/lexicons.html
  http://saifmohammad.com/Lexicons/NRC-Emotion-Lexicon-v0.92.zip
  
  Sentiment dictionary:
    https://www.quora.com/Is-there-a-downloadable-database-of-positive-and-negative-words

sentiment datsets  
    https://www.w3.org/community/sentiment/wiki/Datasets
  
Arabic lang:
  https://sites.google.com/site/datascienceslab/projects/multilingualsentiment
  
  datasets- 
      https://archive.ics.uci.edu/ml/datasets/Twitter+Data+set+for+Arabic+Sentiment+Analysis#
      http://www.mohamedaly.info/datasets
      http://thinknook.com/twitter-sentiment-analysis-training-corpus-dataset-2012-09-22/
  

1) Python NLTK can do Sentiment Analysis based on Classification Algos or NLP tools in it.
2) R has tm.sentiment package which comes with sentiment words and ML based tecniques.
3) Rapidminner, KNIME etc gives classification based on algorithms available in the tool.
3) GATE you can have ML bases (SVM) and rule based or rule + lexion based sentiment analysis
4) OpenNLP provides facility to develop maxent based sentiment analysis
5) Lingpipe provides facility to develop classification based sentiment analysis algos implemented in it
6) Apache Mahout has Naive Bayes and CBayes for classification based Sentiment Analysis
7) Weka has Naive Bayes, SVM, KNN etc.. to develop Sentiment Analysis
8) Python Pattern has Classification algos
9) Python Sklearn has classification algos

To select the best one can do a simple exercise with movie reviews data set using the nine open source tools. Populate a error metrics and can choose one. 

http://breakthroughanalysis.com/2012/01/08/what-are-the-most-powerful-open-source-sentiment-analysis-tools/
http://www.linkedin.com/groups/Open-source-tool-Sentiment-Analysis-2668649.S.190985818
http://www.quora.com/What-are-the-most-powerful-open-source-sentiment-analysis-tools
http://www.quora.com/Sentiment-Analysis/What-are-the-open-source-SDKs-for-entity-extraction-and-sentiment-analysis-in-Java
http://stackoverflow.com/questions/12299724/list-of-natural-language-processing-tools-in-regards-to-sentiment-analysis-whi

GATE -
  http://www.slideshare.net/ahmeda1works/gate-general-architecture-for-text-engineering
  http://www.linkedin.com/groups/Have-anyone-used-GATE-sentiment-2668649.S.134836311
  https://gate.ac.uk/sentiment/
  
  http://www.ranks.nl/stopwords

lexicon approach : http://rua.ua.es/dspace/bitstream/10045/27869/1/PLN_50_11.pdf
Machine learning appraoch : http://www.ijettcs.org/Volume2Issue2/IJETTCS-2013-03-30-051.pdf

http://stackoverflow.com/questions/29575700/good-training-data-for-text-classification-by-lda/29604723#29604723

techniques and tutorial - http://ravikiranj.net/posts/2012/code/how-build-twitter-sentiment-analyzer/