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SINAI at SemEval-2019 Task 6: Incorporating lexicon knowledge into SVM learning to identify and categorize offensive language in social media.

, , , and . SemEval@NAACL-HLT, page 735-738. Association for Computational Linguistics, (2019)

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Sexism Identification in Social Networks using a Multi-Task Learning System., , , and . IberLEF@SEPLN, volume 2943 of CEUR Workshop Proceedings, page 491-499. CEUR-WS.org, (2021)SINAI at SemEval-2019 Task 3: Using affective features for emotion classification in textual conversations., , , and . SemEval@NAACL-HLT, page 307-311. Association for Computational Linguistics, (2019)Improving Spanish Polarity Classification Combining Different Linguistic Resources., , , , , and . NLDB, volume 9103 of Lecture Notes in Computer Science, page 234-245. Springer, (2015)Integrating implicit and explicit linguistic phenomena via multi-task learning for offensive language detection., , , and . Knowl. Based Syst., (2022)Domain Adaptation of Polarity Lexicon combining Term Frequency and Bootstrapping., , , and . WASSA@NAACL-HLT, page 137-146. The Association for Computer Linguistics, (2016)Lexicon Adaptation for Spanish Emotion Mining., , , and . Proces. del Leng. Natural, (2018)SINAI at eRisk@CLEF 2022: Approaching Early Detection of Gambling and Eating Disorders with Natural Language Processing., , , , , and . CLEF (Working Notes), volume 3180 of CEUR Workshop Proceedings, page 961-971. CEUR-WS.org, (2022)SINAI at IberLEF-2021 DETOXIS task: Exploring Features as Tasks in a Multi-task Learning Approach to Detecting Toxic Comments., , , and . IberLEF@SEPLN, volume 2943 of CEUR Workshop Proceedings, page 580-590. CEUR-WS.org, (2021)InLIFE. Tecnologías del Lenguaje aplicadas al envejecimiento activo (InLIFE. Language Technologies applied to active aging)., , , , , , , , , and 1 other author(s). SEPLN (Projects and Demonstrations), volume 3224 of CEUR Workshop Proceedings, page 14-17. CEUR-WS.org, (2022)SINAI at SemEval-2019 Task 6: Incorporating lexicon knowledge into SVM learning to identify and categorize offensive language in social media., , , and . SemEval@NAACL-HLT, page 735-738. Association for Computational Linguistics, (2019)