Hatexplain dataset
WebDec 18, 2024 · HateXplain: A Benchmark Dataset for Explainable Hate Speech Detection. Hate speech is a challenging issue plaguing the online social media. While better models … WebDec 18, 2024 · In this paper, we introduce HateXplain, the first benchmark hate speech dataset covering multiple aspects of the issue. Each post in our dataset is annotated …
Hatexplain dataset
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WebSource Datasets: original. Dataset card Files and versions 1.13.3 hatexplain / README.md. system HF staff ... WebCAVES is the first large-scale dataset containing about 10k COVID-19 anti-vaccine tweets labelled into various specific anti-vaccine concerns in a multi-label setting. This is also the first multi-label classification dataset that provides explanations for each of the labels.
Webprogress. HateXplain is a recently pub-lished and first dataset to use annotated spans in the form of ’rationales’, along with speech classification categories and targeted communities to make the classi-fication more human-like, explainable, ac-curate and less biased. We tune BERT to perform this task in the form of ra- WebAug 9, 2024 · HateXplain is a recently published and first dataset to use annotated spans in the form of rationales, along with speech classification categories and targeted communities to make the classification more humanlike, explainable, accurate and less biased. We tune BERT to perform this task in the form of rationales and class prediction, and ...
WebJun 29, 2024 · Explainable artificial intelligence (XAI) characteristics have flexible and multifaceted potential in hate speech detection by deep learning models. Interpreting and explaining decisions made by complex artificial intelligence (AI) models to understand the decision-making process of these model were the aims of this research. WebDec 18, 2024 · While better models for hate speech detection are continuously being developed, there is little research on the bias and interpretability aspects of hate speech. …
WebApr 12, 2024 · Post_id_divisions has a dictionary having train, valid and test post ids that are used to divide the dataset into train, val and test set in the ratio of 8:1:1. Word2Vec …
Binny Mathew, Punyajoy Saha, Seid Muhie Yimam, Chris Biemann, Pawan Goyal, and Animesh Mukherjee "HateXplain: A Benchmark Dataset for Explainable Hate Speech Detection". Accepted at AAAI 2024. Arxiv paper link. Abstract. Hate speech is a challenging issue plaguing the online social media. While better models for hate speech detection are ... boy silver hairWeb@article{mathew2024hatexplain, title={HateXplain: A Benchmark Dataset for Explainable Hate Speech Detection}, author={Mathew, Binny and Saha, Punyajoy and Yimam, Seid … gwynn whiteWebTo the best of our knowledge, the HateXplain dataset (Mathew et al.,2024) is the only dataset that explic- itlyannotatestargetgroupsfortheclasses"normal" and "offensive" as well, which is why this dataset is the only one that was used to conduct our experi- ments with strictly separated domains. boy silver charmWebIn summary, we introduce HateXplain, the first benchmark dataset for hate speech with word and phrase level span annotations that capture human rationales for the labeling. Using MTurk, we collect a large dataset of around 20K posts and annotate them to cover three aspects of each post. boys images indianWebDatasets: hatexplain Copied like 3 Tasks: Text Classification Languages: English Multilinguality: monolingual Size Categories: 10K<100K Language Creators: crowdsourced Annotations Creators: crowdsourced Source Datasets: original ArXiv: arxiv:2012.10289 arxiv:1703.04009 arxiv:1908.11049 + 1 Tags: hate-speech-detection … gwynn white booksWebPage topic: "HateXplain: A Benchmark Dataset for Explainable Hate Speech Detection". Created by: Willard Phillips. Language: english. gwynn\u0027s store charlestonWebevaluation dataset is shown in Table1. Dataset # Examples HateXplain 1,924 HS18 9,916 Ethos 998 Table 1: Evaluation dataset statistics. 4 Experimental Setup 4.1 Task Decomposition HS detection is a complex and subjective task, and prior work has shown that it is hard to get high agreements between humans about whether or not boys images outline