@inproceedings{814be2efb18244bf88ed1fb1615f0f31,
title = "Merging SenticNet and WordNet-Affect emotion lists for sentiment analysis",
abstract = "SenticNet is currently one of the most comprehensive freely available semantic resources for opinion mining. However, it only provides numerical polarity scores, while more detailed sentiment-related information for its concepts is often desirable. Another important resource for opinion mining and sentiment analysis is WordNet-Affect, which in turn lacks quantitative information. We report a work on automatically merging these two resources by assigning emotion labels to more than 2700 concepts.",
keywords = "Sentic computing, emotions, sentiment analysis",
author = "Soujanya Poria and Alexander Gelbukh and Erik Cambria and Peipei Yang and Amir Hussain and Tariq Durrani",
year = "2012",
doi = "10.1109/ICoSP.2012.6491803",
language = "Ingl{\'e}s",
isbn = "9781467321945",
series = "International Conference on Signal Processing Proceedings, ICSP",
pages = "1251--1255",
booktitle = "ICSP 2012 - 2012 11th International Conference on Signal Processing, Proceedings",
note = "2012 11th International Conference on Signal Processing, ICSP 2012 ; Conference date: 21-10-2012 Through 25-10-2012",
}