@inproceedings{b3244fed62c248cd8e4eea09963293a8,
title = "Sentiment classification using negation as a proxy for negative sentiment",
abstract = "We explore the relationship between negated text and negative sentiment in the task of sentiment classification. We propose a novel adjustment factor based on negation occurrences as a proxy for negative sentiment that can be applied to lexicon-based classifiers equipped with a negation detection pre-processing step. We performed an experiment on a multi-domain customer reviews dataset obtaining accuracy improvements over a baseline, and we further improved our results using out-of-domain data to calibrate the adjustment factor. We see future work possibilities in exploring negation detection refinements, and expanding the experiment to a broader spectrum of opinionated discourse, beyond that of customer reviews.",
author = "Bruno Ohana and Brendan Tierney and Delany, \{Sarah Jane\}",
note = "Publisher Copyright: {\textcopyright} 2016, Association for the Advancement of Artificial Intelligence (www.aaai.org). All rights reserved.; 29th International Florida Artificial Intelligence Research Society Conference, FLAIRS 2016 ; Conference date: 16-05-2016 Through 18-05-2016",
year = "2016",
language = "English",
series = "Proceedings of the 29th International Florida Artificial Intelligence Research Society Conference, FLAIRS 2016",
publisher = "AAAI Press",
pages = "316--321",
editor = "Zdravko Markov and Ingrid Russell",
booktitle = "Proceedings of the 29th International Florida Artificial Intelligence Research Society Conference, FLAIRS 2016",
}