Sentiment Classification Using Negation as a Proxy for Negative Sentiment

Authors

Bruno Ohana, Technological University Dublin
Brendan Tierney, Technological University DublinFollow
Sarah Jane Delany, Technological University DublinFollow

Document Type

Conference Paper

Rights

Available under a Creative Commons Attribution Non-Commercial Share Alike 4.0 International Licence

Disciplines

Computer Sciences

Publication Details

29th. International Florida Artificial Intelligence Research Society Conference

Abstract

We explore the relationship between negated text and neg- ative sentiment in the task of sentiment classification. We propose a novel adjustment factor based on negation occur- rences as a proxy for negative sentiment that can be applied to lexicon-based classifiers equipped with a negation detec- tion 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 nega- tion detection refinements, and expanding the experiment to a broader spectrum of opinionated discourse, beyond that of customer reviews.

Recommended Citation

Ohana, B., Tierney, B. & Delany, S.J. (2016). Sentiment classification using negation as a proxy for negative sentiment.29th. International Florida Artificial Intelligence Research Society Conference