SLIDE - a Sentiment Lexicon of Common Idioms (L18-1)

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Challenge: Compositional solutions for phrase sentiment are not able to handle idioms because their sentiment is not derived from the sentiment of the individual words.
Approach: They propose a crowdsourcing approach for collecting sentiment annotations of idiomatic expressions using crowdsourcing.
Outcome: The proposed approach is able to capture sentiment strength and ambiguity in idiomatic expressions using crowdsourcing.

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Challenge: Identifying and understanding idioms in context is a key goal and challenge in Natural Language Understanding tasks.
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Challenge: idioms are a part of natural language and are difficult to learn with a parallel corpora database.
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Challenge: Potential Idiomatic Expression (PIE) dataset for NLP in English contains over 20,100 samples with almost 1,200 cases of idioms from 10 classes (or senses).
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Challenge: Existing approaches to localize idiomatic expressions have limited views of their generalizability to new idioms.
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Odi et Amo. Creating, Evaluating and Extending Sentiment Lexicons for Latin. (2020.lrec-1)

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Challenge: a new paper aims to provide sentiment analysis tools for ancient languages . the current sentiment analysis resources only cover modern languages based on textual typologies .
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A Thesaurus-based Sentiment Lexicon for Danish: The Danish Sentiment Lexicon (2022.lrec-1)

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Challenge: a newly published Danish sentiment lexicon with a high lexical coverage was compiled using lexicographic methods and linked data.
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