You are here

The Good, the Bad, and the Unknown: Morphosyllabic Sentiment Tagging of Unseen Words

TitleThe Good, the Bad, and the Unknown: Morphosyllabic Sentiment Tagging of Unseen Words
Publication TypeConference Paper
Year of Publication2008
AuthorsMoilanen, K, Pulman, S
Conference Name46th Annual Meeting of the Association for Computational Linguistics on Human Language Technologies
PublisherAssociation for Computational Linguistics
Conference LocationColumbus, Ohio
Abstract

The omnipresence of unknown words is a problem that any NLP component needs to address in some form. While there exist many established techniques for dealing with unknown words in the realm of POS-tagging, for example, guessing unknown words' semantic properties is a less-explored area with greater challenges. In this paper, we study the semantic field of sentiment and propose five methods for assigning prior sentiment polarities to unknown words based on known sentiment carriers. Tested on 2000 cases, the methods mirror human judgements closely in three- and two-way polarity classification tasks, and reach accuracies above 63% and 81%, respectively.

URLhttp://dl.acm.org/citation.cfm?id=1557690.1557719