|Title||The Good, the Bad, and the Unknown: Morphosyllabic Sentiment Tagging of Unseen Words|
|Publication Type||Conference Paper|
|Year of Publication||2008|
|Authors||Moilanen, K, Pulman, S|
|Conference Name||46th Annual Meeting of the Association for Computational Linguistics on Human Language Technologies|
|Publisher||Association for Computational Linguistics|
|Conference Location||Columbus, Ohio|
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.