Paper Info
Title
The good, the bad, and the unknown: morphosyllabic sentiment tagging of unseen words
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.
Year
Venue
Keywords
2008
ACL (Short Papers)
greater challenge,morphosyllabic sentiment,semantic field,known sentiment carrier,prior sentiment polarity,semantic property,nlp component,unseen word,less-explored area,human judgement,established technique,unknown word
Field
DocType
Volume
Omnipresence,Realm,Computer science,Semantic property,Natural language processing,Artificial intelligence,Semantic field,Form of the Good,Machine learning
Conference
P08-2
Citations 
PageRank 
References 
11
0.85
10
Authors
2
Name
Order
Citations
PageRank
Karo Moilanen1212.46
Stephen Pulman245038.31