Generating a Gold Standard for a Swedish Sentiment Lexicon (L18-1)

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Challenge: Existing sentiment lexicons are compiled by (machine) translation from English resources, obscuring language-specific characteristics of sentiment-loaded vocabulary.
Approach: They propose a gold standard for sentiment annotation of Swedish terms using the SALDO lexicon and the Gigaword corpus.
Outcome: The proposed model is based on the free SALDO lexicon and the Gigaword corpus and is compared with existing models using human annotations.

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Challenge: Existing representational frameworks for emotion encoding are incompatible with semantic polarity, resulting in a large amount of incompatible emotion lexicons.
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Challenge: Existing sentiment lexicons reflect abstract notion of polarity and do not do justice to substantial differences of word polarities between domains.
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Sense and Sentiment (2022.lrec-1)

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Challenge: Existing sentiment lexicons and concept-based sentiment-tagged corpora are not accurate, and it is difficult to map sentiment scores accurately to different languages.
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Learning and Evaluating Emotion Lexicons for 91 Languages (2020.acl-main)

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