Sentiment Labelled Sentences Data Set
Padhraic Smyth and Dimitrios Kotzias and Misha Denil and Nando de Freitas

@article{,
title= {Sentiment Labelled Sentences Data Set },
doi= {10.1145/2783258.2783380},
keywords= {},
journal= {ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD)},
author= {Dimitrios Kotzias and Misha Denil and Nando de Freitas and Padhraic Smyth},
year= {2015},
url= {https://archive.ics.uci.edu/dataset/331/sentiment+labelled+sentences},
license= {https://creativecommons.org/licenses/by/4.0/},
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

**Reference:** Kotzias et al., From Group to Individual Labels using Deep Features. KDD 2015, pages 597-606. https://doi.org/10.1145/2783258.2783380},
superseded= {},
terms= {}
}