Sentiment Labelled Sentences Data Set

sentiment labelled sentences.zip 512.21kB
Type: Dataset
Tags:

Metadata:
@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superseded= {},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= {}
}

Citation:
Sentiment Labelled Sentences Data Set . (2016). [Data set]. Academic Torrents. https://academictorrents.com/details/07e05fc1229555e124df72160a01b2540d04cebf
Hosted by users
No stats to report yet.

Send Feedback Start
   0.000006
DB Connect
   0.000514
Lookup hash in DB
   0.000544
Get torrent details
   0.000144
Get torrent details, finished
   0.000232
Get authors
   0.000001
Select authors
   0.000169
Parse bibtex
   0.000167
Write header
   0.000254
get stars
   0.000136
home tab
   0.000160
render right panel
   0.000011
render ads
   0.000631
fetch current hosters
   0.000365
Start get stats
   0.000484
End get stats
   0.000002
related datasets
   0.010486
Done