Create README.md

README.md

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+https://archive.ics.uci.edu/dataset/331/sentiment+labelled+sentences
+
+This dataset was created for the Paper 'From Group to Individual Labels using Deep Features', Kotzias et. al,. KDD 2015
+Please cite the paper if you want to use it :)
+
+It contains sentences labelled with positive or negative sentiment, extracted from reviews of products, movies, and restaurants
+
+=======
+Format:
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+sentence \t score \n
+
+
+=======
+Details:
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+Score is either 1 (for positive) or 0 (for negative)	
+The sentences come from three different websites/fields:
+
+imdb.com
+amazon.com
+yelp.com
+
+For each website, there exist 500 positive and 500 negative sentences. Those were selected randomly for larger datasets of reviews. 
+We attempted to select sentences that have a clearly positive or negative connotaton, the goal was for no neutral sentences to be selected.
+
+
+
+For the full datasets look:
+
+imdb: Maas et. al., 2011 'Learning word vectors for sentiment analysis'
+amazon: McAuley et. al., 2013 'Hidden factors and hidden topics: Understanding rating dimensions with review text'
+yelp: Yelp dataset challenge http://www.yelp.com/dataset_challenge