Verbs Speak Loud: Verb Categories in Learning Polarity and Strength of Opinions

In this work we show that verbs reliably represent texts when machine learning algorithms are used to learn opinions. We identify semantic verb categories that capture essential properties of human communication. Information Extraction methods then are applied to construct verb-based features that represent texts in machine learning experiments. Our empirical results show that expressed actions provide a reliable accuracy in learning opinions.

• Type: Conference
• Year: 2008
• Where: AI
• Authors: Marina Sokolova, Guy Lapalme
• Keywords: AI 2008, Artificial Intelligence, Machine Learning, Machine Learning Algorithms, Semantic Verb Categories