@article{,
title= {Sentiment Labelled Sentences Data Set },
keywords= {},
journal= {},
author= {},
year= {},
url= {},
license= {},
abstract= {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. 

### Format: 
sentence score 

### Details: 
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. 



### Attribute Information:
The attributes are text sentences, extracted from reviews of products, movies, and restaurants


### Relevant Papers:
'From Group to Individual Labels using Deep Features', Kotzias et. al,. KDD 2015
},
superseded= {},
terms= {}
}