SentiEcon is a large, comprehensive, domain-specific computational lexicon designed for sentiment analysis applications, which we compiled from our own corpus of online business news. SentiEcon was created as a plug-in lexicon for the sentiment analysis tool Lingmotif, and thus it follows its data structure requirements and presupposes the availability of a general-language core sentiment lexicon that covers non-specific sentiment-carrying terms and phrases. It contains over 6,800 entries, both single and multi-word expressions, each with tags denoting their semantic orientation and intensity. We evaluate SentiEcon’s performance by comparing results in a sentence classification task using exclusively sentiment words as features. This sentence dataset was extracted from business news texts, and included certain key words known to recurrently convey strong semantic orientation, such as debt, inflation or markets. The results show that performance is significantly improved when adding SentiEcon to the general-language sentiment lexicon.

Creator(s)

Javier Fernandez-Cruz

Distributor(s)

Javier Fernandez-Cruz

Right Holder(s)

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