Generating High-Coverage Semantic Orientation Lexicons From Overtly Marked Words and a Thesaurus

Sentiment analysis often relies on a semantic orientation lexicon of positive and negative words. A number of approaches have been proposed for creating such lexicons, but they tend to be computationally expensive, and usually rely on significant manual annotation and large corpora. Most of these methods use WordNet. In contrast, we propose a simple approach to generate a high-coverage semantic orientation lexicon, which includes both individual words and multi-word expressions, using only a Roget-like thesaurus and a handful of affixes. Further, the lexicon has properties that support the Polyanna Hypothesis. Using the General Inquirer as gold standard, we show that our lexicon has 14 percentage points more correct entries than the leading WordNet-based high-coverage lexicon (SentiWordNet). In an extrinsic evaluation, we obtain significantly higher performance in determining phrase polarity using our thesaurus-based lexicon than with any other. Additionally, we explore the use of vis...

• Type: Journal
• Year: 2009
• Where: EMNLP
• Authors: Saif Mohammad, Cody Dunne, Bonnie J. Dorr
• Keywords: EMNLP 2009, Lexicon, Natural Language Processing, Semantic Orientation Lexicon, Significant Manual Annotation