More than words

A strong predictive connection between linguistically well motivated features and implicit sentiment is established, and it is shown how computational approximations of these features can be used to improve on existing state-of-the-art sentiment classification results.

Abstract

Work on sentiment analysis often focuses on the words and phrases that people use in overtly opinionated text. In this paper, we introduce a new approach to the problem that focuses not on lexical indicators, but on the syntactic "packaging" of ideas, which is well suited to investigating the identification of implicit sentiment, or perspective. We establish a strong predictive connection between linguistically well motivated features and implicit sentiment, and then show how computational approximations of these features can be used to improve on existing state-of-the-art sentiment classification results.