Learning Good Opinions from Just Two Words Is Not Bad
Darius Andrei Suciu, Vlad Vasile Itu, Alexandru Cristian Cosma, Mihaela Dinsoreanu, Rodica Potolea
2014
Abstract
Considering the wide spectrum of both practical and research applicability, opinion mining has attracted increased attention in recent years. This article focuses on breaking the domain-dependency issues which occur in supervised opinion mining by using an unsupervised approach. Our work devises a methodology by considering a set of grammar rules for identification of opinion bearing words. Moreover, we focus on tuning our method for the best tradeoff between precision-recall, computation complexity and number of seed words while not committing to a specific input data set. The method is general enough to perform well using just 2 seed words therefore we can state that it is an unsupervised strategy. Moreover, since the 2 seed words are class representatives (“good”, “bad”) we claim that the method is domain independent.
References
- Guang Qiu, Bing Liu, Jiajun Bu, Chun Chen 2012. Opinion Word Expansion and Target Extraction through Double Propagation. In Computational Linguistics, March 2011, Vol. 37, No. 1: 9.27.
- Turney, Peter D. 2002. Thumbs up or thumbs down? Semantic orientation applied to unsupervised classification of reviews. In Proceedings of ACL'02, pages 417-424.
- Hatzivassiloglou, Vasileios and Hathleen R. McKeown. 1997. Predicting the semantic orientation of adjectives. In Proceedings of ACL'97, pages 174-181. Stroudsburg, PA.
- Hu, Mingqing and Bing Liu. 2004. Mining and summarizing customer reviews. In Proceedings of SIGKDD'04, pages 168-177.
- Popescu, Ana-Maria and Oren Etzioni. 2005. Extracting product features and opinions from reviews. In Proceedings of EMNLP'05, pages 339-346.
- Brill, E. 1994. Some advances in transformation-based part of speech tagging. Proceedings of the Twelfth National Conference on Artificial Intelligence (pp.722-727). Menlo Park, CA: AAAI Press.
- Jin, H. H. Ho, and R. K. Srihari, OpinionMiner: a novel machine learning system for web opinion mining and extraction, presented at the Proceedings of the 15thACM SIGKDD international conference on Knowledge discovery and data mining, Paris, France, 2009.
- Htay, Su Su, and Khin Thidar Lynn, 2013. Extracting product features and opinion words using pattern knowledge in customer reviews. The Scientific World Journal.
- Baccianella, Stefano, Andrea Esuli, and Fabrizio Sebastiani, 2010. SentiWordNet 3.0: An Enhanced Lexical Resource for Sentiment Analysis and Opinion Mining. Seventh conference on Iternational Language Resources and Evaluation.
- Xia Hu, Jiliang Tang, Huiji Gao, 2013. Unsupervised Sentiment Analysis with Emotional Signals. Proceedings of the 22nd international conference on World Wide Web. 607-618.
- Zhang, Lei, Bing Liu, Suk Hwan Lim, and Eamonn OBrien-Strain, 2010. Extracting and Ranking Product Features in Opinion Documents. International Conference on Computational Linquistics. 1462-1470.
- Marco Guerini, Lorenzo Gatti and Marco Turchi, 2013. Sentiment Analysis: How to Derive Prior Polarities from SentiWordNet. arXiv Preprint, arXiv:1309.5843.
- Edison Marrese-Taylor, Juan D. Velasquez, Felipe BravoMarquez, 2013. OpinionZoom, a modular tool to explore tourism opinions on the Web. ACM International Conferences on Web Intelligence and Intelligent Agent Technology. 261-264.
- Maite Taboada, Caroline Anthony and Kimberly Voll, 2006. Methods for Creating Semantic Orientation Dictionaries. Proceedings of 5th International Conference on Language Resources and Evaluation (LREC). 427-432.
- Christopher D. Manning, 2011. Part-of-Speech Tagging from 97% to 100%: Is It Time for Some Linguistics?. Proceedings of the 12th International Conference on Computational Linguistics and Intelligent Text Processing, 171-189.
- Cosma Alexandru et all, 2014. Overcoming the domain barrier in opinion extraction. Accepted for publication at 10th International Conference on Intelligent Computer Communication and Processing.
Paper Citation
in Harvard Style
Suciu D., Itu V., Cosma A., Dinsoreanu M. and Potolea R. (2014). Learning Good Opinions from Just Two Words Is Not Bad . In Proceedings of the International Conference on Knowledge Discovery and Information Retrieval - Volume 1: KDIR, (IC3K 2014) ISBN 978-989-758-048-2, pages 233-241. DOI: 10.5220/0005079802330241
in Bibtex Style
@conference{kdir14,
author={Darius Andrei Suciu and Vlad Vasile Itu and Alexandru Cristian Cosma and Mihaela Dinsoreanu and Rodica Potolea},
title={Learning Good Opinions from Just Two Words Is Not Bad},
booktitle={Proceedings of the International Conference on Knowledge Discovery and Information Retrieval - Volume 1: KDIR, (IC3K 2014)},
year={2014},
pages={233-241},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005079802330241},
isbn={978-989-758-048-2},
}
in EndNote Style
TY - CONF
JO - Proceedings of the International Conference on Knowledge Discovery and Information Retrieval - Volume 1: KDIR, (IC3K 2014)
TI - Learning Good Opinions from Just Two Words Is Not Bad
SN - 978-989-758-048-2
AU - Suciu D.
AU - Itu V.
AU - Cosma A.
AU - Dinsoreanu M.
AU - Potolea R.
PY - 2014
SP - 233
EP - 241
DO - 10.5220/0005079802330241