Toward a perspectivist turn in ground truthing for predictive computing
Abstract Most current Artificial Intelligence applications are based on supervised Machine
Learning (ML), which ultimately grounds on data annotated by small teams of experts or …
Learning (ML), which ultimately grounds on data annotated by small teams of experts or …
I beg to differ: how disagreement is handled in the annotation of legal machine learning data sets
D Braun - Artificial intelligence and law, 2024 - Springer
Legal documents, like contracts or laws, are subject to interpretation. Different people can
have different interpretations of the very same document. Large parts of judicial branches all …
have different interpretations of the very same document. Large parts of judicial branches all …
Online conspiracy communities are more resilient to deplatforming
Online social media foster the creation of active communities around shared narratives.
Such communities may turn into incubators for conspiracy theories—some spreading violent …
Such communities may turn into incubators for conspiracy theories—some spreading violent …
Subjective crowd disagreements for subjective data: Uncovering meaningful CrowdOpinion with population-level learning
TC Weerasooriya, S Luger, S Poddar… - arXiv preprint arXiv …, 2023 - arxiv.org
Human-annotated data plays a critical role in the fairness of AI systems, including those that
deal with life-altering decisions or moderating human-created web/social media content …
deal with life-altering decisions or moderating human-created web/social media content …
HateDay: Insights from a Global Hate Speech Dataset Representative of a Day on Twitter
To tackle the global challenge of online hate speech, a large body of research has
developed detection models to flag hate speech in the sea of online content. Yet, due to …
developed detection models to flag hate speech in the sea of online content. Yet, due to …
HateSieve: A Contrastive Learning Framework for Detecting and Segmenting Hateful Content in Multimodal Memes
Amidst the rise of Large Multimodal Models (LMMs) and their widespread application in
generating and interpreting complex content, the risk of propagating biased and harmful …
generating and interpreting complex content, the risk of propagating biased and harmful …
Integrated gradients as proxy of disagreement in hateful content
Online platforms have increasingly become hotspots to spread not only opinions but also
hate speech, posing substantial obstacles to developing constructive and inclusive online …
hate speech, posing substantial obstacles to developing constructive and inclusive online …
A sentiment corpus for the cryptocurrency financial domain: the CryptoLin corpus
MFA Gadi, MÁ Sicilia - Language Resources and Evaluation, 2024 - Springer
The objective of this paper is to describe Cryptocurrency Linguo (CryptoLin), a novel corpus
containing 2683 cryptocurrency-related news articles covering more than a three-year …
containing 2683 cryptocurrency-related news articles covering more than a three-year …
Deep learning based multilabel hateful speech text comments recognition and classification model for resource scarce ethiopian language: The case of afaan oromo
NB Defersha, J Abawajy… - 2022 IEEE International …, 2022 - ieeexplore.ieee.org
In response to the phenomenon of hate speech on popular social media such as Facebook,
a number of researchers have investigated and developed different automated techniques …
a number of researchers have investigated and developed different automated techniques …
A Study of Slang Representation Methods
Considering the large amount of content created online by the minute, slang-aware
automatic tools are critically needed to promote social good, and assist policymakers and …
automatic tools are critically needed to promote social good, and assist policymakers and …