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Journalistic Relevance Classification in Social Network Messages: an Exploratory Approach.

, , , and . COMPLEX NETWORKS, volume 693 of Studies in Computational Intelligence, page 631-642. Springer, (2016)

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Journalistic Relevance Classification in Social Network Messages: an Exploratory Approach., , , and . COMPLEX NETWORKS, volume 693 of Studies in Computational Intelligence, page 631-642. Springer, (2016)Merging Datasets for Hate Speech Classification in Italian., , and . EVALITA@CLiC-it, volume 2263 of CEUR Workshop Proceedings, CEUR-WS.org, (2018)A Survey on Automatic Detection of Hate Speech in Text., and . ACM Comput. Surv., 51 (4): 85:1-85:30 (2018)Re-thinking large scale hate speech identification: beyond common NLP conventions and supervised machine learning. Pompeu Fabra University, Spain, (2023)Toxic, Hateful, Offensive or Abusive? What Are We Really Classifying? An Empirical Analysis of Hate Speech Datasets., , and . LREC, page 6786-6794. European Language Resources Association, (2020)An Approach to Relevancy Detection: Contributions to the Automatic Detection of Relevance in Social Networks., , and . WorldCIST (1), volume 444 of Advances in Intelligent Systems and Computing, page 89-99. Springer, (2016)How well do hate speech, toxicity, abusive and offensive language classification models generalize across datasets?, , and . Inf. Process. Manag., 58 (3): 102524 (2021)Stop PropagHate at SemEval-2019 Tasks 5 and 6: Are abusive language classification results reproducible?, , and . SemEval@NAACL-HLT, page 745-752. Association for Computational Linguistics, (2019)Directions for NLP Practices Applied to Online Hate Speech Detection., , , and . EMNLP, page 11794-11805. Association for Computational Linguistics, (2022)Motivators and Deterrents for Data Description and Publication: Preliminary Results (Short Paper)., , , , and . OTM Workshops, volume 9416 of Lecture Notes in Computer Science, page 512-516. Springer, (2015)