Confronting abusive language online: A survey from the ethical and human rights perspective

S Kiritchenko, I Nejadgholi, KC Fraser - Journal of Artificial Intelligence …, 2021 - jair.org
The pervasiveness of abusive content on the internet can lead to severe psychological and
physical harm. Significant effort in Natural Language Processing (NLP) research has been …

Surfacing racial stereotypes through identity portrayal

G Kambhatla, I Stewart, R Mihalcea - … of the 2022 ACM conference on …, 2022 - dl.acm.org
Content warning: this paper discusses and contains content that may be offensive or
upsetting. People express racial stereotypes through conversations with others, increasingly …

Is Carla grumpy? Analysis of peer evaluations to explore microaggressions and other marginalizing behaviors in engineering student teams

DA Dickerson, S Masta, MW Ohland… - Journal of Engineering …, 2024 - Wiley Online Library
Background Teamwork has become a central element of engineering education. However,
the race‐and gender‐based marginalization prevalent in society is also prevalent in …

Lung cancer classification using convolutional neural network and DenseNet

NP Damayanti, MND Ananda… - Journal of Soft …, 2023 - shmpublisher.com
Lung cancer is a condition that has a major impact on public health. Convolutional Neural
Network (CNN) and DenseNet approaches are suggested in this study to aid lung cancer …

Abusive words Detection in Persian tweets using machine learning and deep learning techniques

M Dehghani, DT Dehkordy… - 2021 7th International …, 2021 - ieeexplore.ieee.org
Regarding the development of the web and increasing user interaction, different users'
opinions about different phenomena have been observed. In recent years, the detection of …

Linguistic and vocal markers of microbehaviors between team members during analog space exploration missions

P Paromita, A Khader, S Begerowski… - IEEE Pervasive …, 2023 - ieeexplore.ieee.org
We used machine learning classifiers and dialog state tracking models, combined with
natural language processing techniques relying on lexicon-based methods and data-driven …

Leveraging bias in pre-trained word embeddings for unsupervised microaggression detection

N Sabri, V Basile, T Caselli - Italian Conference on Computational …, 2021 - research.rug.nl
Microaggressions are subtle manifestations of bias (Breitfeller et al., 2019). These
demonstrations of bias can often be classified as a subset of abusive language. However …

Beyond Justice: Artificial Intelligence and the Value of Community

J Viehoff - 2022 - academic.oup.com
Most discussions in the field of artificial intelligence (AI) ethics concern the avoidance of
individual wrongs like discrimination, the violation of privacy, or algorithmic unfairness …

[HTML][HTML] Perspective Chapter: Emotion Detection Using Speech Analysis and Deep Learning

AI Iliev - … Recognition-Recent Advances, New Perspectives and …, 2023 - intechopen.com
Speech reflects the sentiment and emotions of humans. People can identify the emotional
states in speech utterances, but there is a higher chance of perception error, which is …

Towards Identification of Microaggressions in real-life and Scripted conversations, using Context-Aware Machine Learning Techniques.

MK Ngueajio, I Hernandez, K Cornett, G Washington - 2023 - openreview.net
The advent and rapid proliferation of social media have brought with it an exponential
growth in hate speech and overt offensive language, with one of the most subtle yet …