Lexicon-Based methods for sentiment analysis
- We present a lexicon-based approach to extracting sentiment from text. The Semantic Orientation CALculator (SO-CAL) uses dictionaries of words annotated with their semantic orientation (polarity and strength), and incorporates intensification and negation. SO-CAL is applied to the polarity classification task, the process of assigning a positive or negative label to a text that captures the text's opinion towards its main subject matter. We show that SO-CAL's performance is consistent across domains and on completely unseen data. Additionally, we describe the process of dictionary creation, and our use of Mechanical Turk to check dictionaries for consistency and reliability.
Author details: | Maite Taboada, Julian Brooke, Milan Tofiloski, Kimberly Voll, Manfred StedeORCiDGND |
---|---|
ISSN: | 0891-2017 |
Title of parent work (English): | Computational linguistics |
Publisher: | MIT Press |
Place of publishing: | Cambridge |
Publication type: | Article |
Language: | English |
Year of first publication: | 2011 |
Publication year: | 2011 |
Release date: | 2017/03/26 |
Volume: | 37 |
Issue: | 2 |
Number of pages: | 41 |
First page: | 267 |
Last Page: | 307 |
Funding institution: | Natural Sciences and Engineering Research Council of Canada [261104-2008]; Social Sciences and Humanities Research Council of Canada [410-2006-1009] |
Organizational units: | Humanwissenschaftliche Fakultät / Strukturbereich Kognitionswissenschaften / Department Linguistik |
Peer review: | Referiert |
Publishing method: | Open Access |
Institution name at the time of the publication: | Humanwissenschaftliche Fakultät / Institut für Linguistik / Allgemeine Sprachwissenschaft |