Skip to content

Don't Count, Predict! An Automatic Approach to Learning Sentiment Lexicons for Short Text

Notifications You must be signed in to change notification settings

duytinvo/acl2016

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

9 Commits
 
 
 
 
 
 
 
 

Repository files navigation

acl2016

This code is used for the paper "Don't Count, Predict! An Automatic Approach to Learning Sentiment Lexicons for Short Text" (ACL2016-short paper)

This repository consists of three folders:

  • learn_lexicon: scripts to learn lexicons
  • test_lexicon: scripts to test ours learned lexicons
  • lexicons: sentiment lexicons in English and Arabic, which are learned by our models.

To use our lexicons:

  • English and Arabic lexicons in "lexicons" folder.
  • Data format: word + '\t' + sentiment score + '\n'

To compare our lexicons with available lexicons:

  • Change current directory to folder "acl2016/test_lexicon/scripts"
  • Change all *.sh file to 755 (e.g. chmod 755 *.sh)
  • Change all files in folder liblinear to 755 (e.g. chmod 755 ./liblinear/*)
  • For testing English lexicons:
    • Extract features: ./run_features.sh
    • Classification: ./run_liblinear.sh
  • For testing Arabic lexicons:
    • Extract features: ./run_features_ar.sh
    • Classification: ./run_liblinear_ar.sh

To run the our models to learn lexicons:

TO LEARN MODEL BY YOUR OWN DATA:

  • Process your data:
    • Example: python process.py ../data/alexgo/raw/metatweets ../data/alexgo/processed/info.tw ../data/alexgo/processed/process.tw
    • Raw data format: labels (1 or 0) + ' ' + tweet +'\n'
  • Modify the script by changing the inputs to ../data/alexgo/processed/info.tw and ../data/alexgo/processed/process.tw
  • Run model

Reference:

@InProceedings{vo-zhang:2016:acl,

author = {Vo, Duy Tin and Zhang, Yue},

title = {Don't Count, Predict! An Automatic Approach to Learning Sentiment Lexicons for Short Text},

booktitle = {Proceedings of ACL},

month = {August},

year = {2016},

address = {Berlin, Germany}}

About

Don't Count, Predict! An Automatic Approach to Learning Sentiment Lexicons for Short Text

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published