Lingmotif-lex: a Wide-coverage, State-of-the-art Lexicon for Sentiment Analysis (L18-1)

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Challenge: Sentiment Analysis is a subtask of Natural Language Processing.
Approach: They propose a new, domain-neutral lexicon for sentiment analysis in English . they test it on two publicly available sentiment analysis datasets .
Outcome: The proposed lexicon performs better than existing sentiment lexiconics on two publicly available datasets.

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Representation Mapping: A Novel Approach to Generate High-Quality Multi-Lingual Emotion Lexicons (L18-1)

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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.
Approach: They propose to map different emotion representation formats onto each other for mutual compatibility and interoperability of language resources.
Outcome: The proposed method produces (near-)gold quality emotion lexicons even in crosslingual settings.
Design and Evaluation of SentiEcon: a fine-grained Economic/Financial Sentiment Lexicon from a Corpus of Business News (2020.lrec-1)

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Challenge: SentiEcon is a large, comprehensive, domain-specific computational lexicon designed for sentiment analysis applications.
Approach: They describe a large, comprehensive, domain-specific computational lexicon designed for sentiment analysis applications.
Outcome: The proposed lexicon significantly improves when adding sentiment words to the general-language sentiment lexiconic.
Learning and Evaluating Emotion Lexicons for 91 Languages (2020.acl-main)

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Challenge: Emotion lexicons describe the affective meaning of words but are limited in coverage for most languages.
Approach: They propose a method for creating arbitrarily large emotion lexicons for any target language.
Outcome: The proposed method exceeds human reliability for some languages and variables.
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 .
Approach: They propose to use manually-curated Latin lexicons to evaluate sentiment analysis tools . they propose a gold standard and a silver standard for evaluating lexical items .
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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.
Approach: They propose to use lexicographic methods to compile a Danish sentiment lexicon with a high lexical coverage by linking words from a thesaurus to a comprehensive monolingual dictionary.
Outcome: The proposed lexicon contains 13,859 Danish polarity lemmas and includes morphological information.
Cross-Lingual Emotion Lexicon Induction using Representation Alignment in Low-Resource Settings (2020.coling-main)

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Challenge: Emotion lexicons provide information about associations between words and emotions.
Approach: They use crowdsourcing to annotate words with Plutchik's 8 basic emotions, providing binary labels.
Outcome: The proposed lexicons provide information about associations between words and emotions . the lexiconics are useful in emotional analyses of reviews, literary texts, and posts on social media .
Classifier-based Polarity Propagation in a WordNet (L18-1)

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Challenge: a wordnet-based sentiment lexicon can be built to express sentiment polarity in a way shared across domains.
Approach: They propose a method to build a sense-level sentiment lexicon on the basis of a wordnet . they use a rich set of wordnet-based features to recognize and assign sentiment polarity values .
Outcome: The proposed method allows for the construction of a more reliable sentiment lexicon . the proposed method is partially automated, but it's performance drops in cross-domain applications .
Introducing Lexical Masks: a New Representation of Lexical Entries for Better Evaluation and Exchange of Lexicons (2020.lrec-1)

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Challenge: Existing standards for lexicon format and features are inadequate for evaluation and exchange . lexical masks are a powerful tool used to evaluate and exchange large lexiconic databases .
Approach: They propose a tool to evaluate and exchange lexicon databases in many languages . they propose lexical masks which represent the expected internal structure of a lexico .
Outcome: The proposed lexical masks can be used to evaluate and exchange lexicon databases in many languages.
Lexi: A tool for adaptive, personalized text simplification (C18-1)

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Challenge: Existing research on text simplification has aimed to develop generic solutions . instead, we need to develop customized simplification systems for individual users .
Approach: They propose a framework for adaptive lexical simplification and introduce Lexi, a free open-source tool for personalized text simplification.
Outcome: The proposed framework is based on a free open-source tool for adaptive, personalized text simplification.
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.
Approach: They examine existing sentiment lexicons and sense-based sentiment-tagged corpora to find out how sense and concept-based semantic relations effect sentiment scores.
Outcome: The proposed lexicon can be used to generate sentiment lexicos for English using the Open Multilingual Wordnet.

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