| Abstract | Most past work on determining the strength of subjective expres-sions within a sentence or a document use specific parts of speech
such as adjectives, verbs and nouns. To date, there is almost no
work on the use of adverbs in sentiment analysis, nor has there been
any work on the use of adverb-adjective combinations (AACs). We
propose an AAC-based sentiment analysis technique that uses a lin-
guistic analysis of adverbs of degree. We define a set of general
axioms (based on a classification of adverbs of degree into five cat-
egories) that all adverb scoring techniques must satisfy. Instead of
aggregating scores of both adverbs and adjectives using simple scor-
ing functions, we propose an axiomatic treatment of AACs based
on the linguistic classification of adverbs. Three specific AAC scor-
ing methods that satisfy the axioms are presented. We describe the
results of experiments on an annotated set of 200 news articles (an-
notated by 10 students) and compare our algorithms with some exist-
ing sentiment analysis algorithms. We show that our results lead to
higher accuracy based on Pearson correlation with human subjects.
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