Generating Semantic Orientation Lexicon using Large Data and Thesaurus

We propose a novel method to construct semantic orientation lexicons using large data and a thesaurus. To deal with large data, we use Count-Min sketch to store the approximate counts of all word pairs in a bounded space of 8GB. We use a thesaurus (like Roget) to constrain near-synonymous words to have the same polarity. This framework can easily scale to any language with a thesaurus and a unzipped corpus size 50 GB (12 billion tokens). We evaluate these lexicons intrinsically and extrinsically, and they perform comparable when compared to other existing lexicons.

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