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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Hits 1 – 5 of 5 1 Monolingual and Cross-Lingual Acceptability Judgments with the Italian CoLA corpus ... Trotta, Daniela; Guarasci, Raffaele; Leonardelli, Elisa. - : arXiv, 2021 BASE Show details 2 Agreeing to Disagree: Annotating Offensive Language Datasets with Annotators' Disagreement ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Guerini, Marco; Leonardelli, Elisa; Menini, Stefano; Palmero Aprosio, Alessio; Tonelli, Sara. - : Underline Science Inc., 2021 Abstract: Anthology paper link: https://aclanthology.org/2021.emnlp-main.822/ Abstract: Since state-of-the-art approaches to offensive language detection rely on supervised learning, it is crucial to quickly adapt them to the continuously evolving scenario of social media. While several approaches have been proposed to tackle the problem from an algorithmic perspective, so to reduce the need for annotated data, less attention has been paid to the quality of these data. Following a trend that has emerged recently, we focus on the level of agreement among annotators while selecting data to create offensive language datasets, a task involving a high level of subjectivity. Our study comprises the creation of three novel datasets of English tweets covering different topics and having five crowd-sourced judgments each. We also present an extensive set of experiments showing that selecting training and test data according to different levels of annotators' agreement has a strong effect on classifiers performance and ... Keyword: Computational Linguistics; Machine Learning; Machine Learning and Data Mining; Natural Language Processing URL: https://underline.io/lecture/37766-agreeing-to-disagree-annotating-offensive-language-datasets-with-annotators'-disagreement https://dx.doi.org/10.48448/w49c-2969 BASE Hide details 3 Monolingual and Cross-Lingual Acceptability Judgments with the Italian CoLA corpus ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Guarasci, Raffaele; Leonardelli, Elisa. - : Underline Science Inc., 2021 BASE Show details 4 Spatiotemporal properties of the neural representation of conceptual content for words and pictures – an MEG study Giari, Giuliano; Leonardelli, Elisa; Tao, Yuan... In: Neuroimage (2020) BASE Show details 5 Temporal dynamics of access to amodal representations of category-level conceptual information Leonardelli, Elisa; Fait, Elisa; Fairhall, Scott L.. - : Nature Publishing Group UK, 2019 BASE Show details

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