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Can Character-based Language Models Improve Downstream Task Performance in Low-Resource and Noisy Language Scenarios?
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In: Seventh Workshop on Noisy User-generated Text (W-NUT 2021, colocated with EMNLP 2021) ; https://hal.inria.fr/hal-03527328 ; Seventh Workshop on Noisy User-generated Text (W-NUT 2021, colocated with EMNLP 2021), Jan 2022, punta cana, Dominican Republic ; https://aclanthology.org/2021.wnut-1.47/ (2022)
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Cross-lingual few-shot hate speech and offensive language detection using meta learning
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In: ISSN: 2169-3536 ; EISSN: 2169-3536 ; IEEE Access ; https://hal.archives-ouvertes.fr/hal-03559484 ; IEEE Access, IEEE, 2022, 10, pp.14880-14896. ⟨10.1109/ACCESS.2022.3147588⟩ (2022)
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Ensemble of Opinion Dynamics Models to Understand the Role of the Undecided in the Vaccination Debate ...
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The Online Behaviour of the Algerian Abusers in Social Media Networks ...
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Discussion Networks and Resilience of College Students: Explicating Tie Strength in Communicative Interaction
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In: International Journal of Communication; Vol 16 (2022); 25 ; 1932-8036 (2022)
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“Thou Shalt Not Take the Lord’s Name in Vain”: A Methodological Proposal to Identify Religious Hate Content on Digital Social Networks
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In: International Journal of Communication; Vol 16 (2022); 22 ; 1932-8036 (2022)
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Conceptual structure and the growth of scientific knowledge ...
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INNOVATIVE APPROACHES AND METHODS IN TEACHING FOREIGN LANGUAGES ...
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INNOVATIVE APPROACHES AND METHODS IN TEACHING FOREIGN LANGUAGES ...
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Multilingual Abusiveness Identification on Code-Mixed Social Media Text ...
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MuMiN: A Large-Scale Multilingual Multimodal Fact-Checked Misinformation Social Network Dataset ...
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Discovering Affinity Relationships between Personality Types ...
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Networks and Identity Drive Geographic Properties of the Diffusion of Linguistic Innovation ...
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Cyberbullying Classifiers are Sensitive to Model-Agnostic Perturbations ...
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Abstract:
A limited amount of studies investigates the role of model-agnostic adversarial behavior in toxic content classification. As toxicity classifiers predominantly rely on lexical cues, (deliberately) creative and evolving language-use can be detrimental to the utility of current corpora and state-of-the-art models when they are deployed for content moderation. The less training data is available, the more vulnerable models might become. This study is, to our knowledge, the first to investigate the effect of adversarial behavior and augmentation for cyberbullying detection. We demonstrate that model-agnostic lexical substitutions significantly hurt classifier performance. Moreover, when these perturbed samples are used for augmentation, we show models become robust against word-level perturbations at a slight trade-off in overall task performance. Augmentations proposed in prior work on toxicity prove to be less effective. Our results underline the need for such evaluations in online harm areas with small ... : Submitted to LREC 2022 ...
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Keyword:
Computation and Language cs.CL; Computers and Society cs.CY; FOS Computer and information sciences; Social and Information Networks cs.SI
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URL: https://arxiv.org/abs/2201.06384 https://dx.doi.org/10.48550/arxiv.2201.06384
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Feature-rich multiplex lexical networks reveal mental strategies of early language learning ...
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It Takes a Village: Using Network Science to Identify the Effect of Individual Differences in Bilingual Experience for Theory of Mind
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In: Brain Sciences; Volume 12; Issue 4; Pages: 487 (2022)
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Analysis of the Full-Size Russian Corpus of Internet Drug Reviews with Complex NER Labeling Using Deep Learning Neural Networks and Language Models
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In: Applied Sciences; Volume 12; Issue 1; Pages: 491 (2022)
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Transformer-Based Abstractive Summarization for Reddit and Twitter: Single Posts vs. Comment Pools in Three Languages
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In: Future Internet; Volume 14; Issue 3; Pages: 69 (2022)
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