The field of sentiment analysis or opinion mining consists in automatically classifying text according to the positive or negative sentiment expressed in it, and has become very popular in the last decade. However, most data and software resources are built for English and a few other languages. In this paper we compare and test different corpus-based and lexicon-based methods for creating a sentiment lexicon. We then manually curate the results of the best performing method. The result, SenSALDO, is a comprehensive sentiment lexicon for Swedish containing 7,618 word senses as well as a full-form version of this lexicon containing 65,953 items (text word forms). SenSALDO is freely available as a research tool in the SWE-CLARIN toolbox under an open-source CC-BY license.
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