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SenSALDO: Creating a Sentiment Lexicon for Swedish

Conference paper
Authors Jacobo Rouces
Nina Tahmasebi
Lars Borin
Stian Rødven Eide
Published in To appear in Language Resources and Evaluation Conference (LREC 2018)
Publication year 2018
Published at Department of Literature, History of Ideas, and Religion
Department of Swedish
Language en
Keywords Sentiment analysis, Swedish, lexicon, lexical resource
Subject categories Languages and Literature, Language Technology (Computational Linguistics)


The natural language processing subfield known as sentiment analysis or opinion mining has seen an explosive expansion over the last decade or so, and sentiment analysis has become a standard item in the NLP toolbox. Still, many theoretical and methodological questions remain unanswered and resource gaps unfilled. Most work on automated sentiment analysis has been done on English and a few other languages; for most written languages of the world, this tool is not available. This paper describes the development of an extensive sentiment lexicon for written (standard) Swedish. We investigate different methods for developing a sentiment lexicon for Swedish. We use an existing gold standard dataset for training and testing. For each word sense from the SALDO Swedish lexicon, we assign a real value sentiment score in the range [-1,1] and produce a sentiment label. We implement and evaluate three methods: a graph-based method that iterates over the SALDO structure, a method based on random paths over the SALDO structure and a corpus-driven method based on word embeddings. The resulting sense-disambiguated sentiment lexicon (SenSALDO) is an open source resource and freely available from Språkbanken, The Swedish Language Bank at the University of Gothenburg.

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