|
|
|
|
|
Andrei Paraschiv, Teodora Andreea Ion and Mihai Dascalu
The advent of online platforms and services has revolutionized communication, enabling users to share opinions and ideas seamlessly. However, this convenience has also brought about a surge in offensive and harmful language across various communication m...
ver más
|
|
|
|
|
|
|
|
|
|
|
Khalil Al-Hussaeni, Mohamed Sameer and Ioannis Karamitsos
Due to the increasing reliance on social network platforms in recent years, hate speech has risen significantly among online users. Government and social media platforms face the challenging responsibility of controlling, detecting, and removing massivel...
ver más
|
|
|
|
|
|
|
|
|
|
|
Alejandro Molina-Villegas, Thomas Cattin, Karina Gazca-Hernandez and Edwin Aldana-Bobadilla
Currently, a significant portion of published research on online hate speech relies on existing textual corpora. However, when examining a specific context, there is a lack of preexisting datasets that include the particularities associated with various ...
ver más
|
|
|
|
|
|
|
|
|
|
|
Shilpa Gite, Shruti Patil, Deepak Dharrao, Madhuri Yadav, Sneha Basak, Arundarasi Rajendran and Ketan Kotecha
Feature selection and feature extraction have always been of utmost importance owing to their capability to remove redundant and irrelevant features, reduce the vector space size, control the computational time, and improve performance for more accurate ...
ver más
|
|
|
|
|
|
|
|
|
|
|
Charalampos A. Dimoulas and Andreas Veglis
We live in a digital era, with vast technological advancements, which, among others, have a major impact on the media domain. More specifically, progress in the last two decades led to the end-to-end digitalization of the media industry, resulting in a r...
ver más
|
|
|
|
|
|
|
|
|
|
|
Ashokkumar Palanivinayagam, Claude Ziad El-Bayeh and Robertas Dama?evicius
Machine-learning-based text classification is one of the leading research areas and has a wide range of applications, which include spam detection, hate speech identification, reviews, rating summarization, sentiment analysis, and topic modelling. Widely...
ver más
|
|
|
|
|
|
|
|
|
|
|
Amr Mohamed El Koshiry, Entesar Hamed I. Eliwa, Tarek Abd El-Hafeez and Ahmed Omar
Social media platforms have become the primary means of communication and information sharing, facilitating interactive exchanges among users. Unfortunately, these platforms also witness the dissemination of inappropriate and toxic content, including hat...
ver más
|
|
|
|
|
|
|
|
|
|
|
Donia Gamal, Marco Alfonse, Salud María Jiménez-Zafra and Mostafa Aref
Sentiment Analysis, also known as opinion mining, is the area of Natural Language Processing that aims to extract human perceptions, thoughts, and beliefs from unstructured textual content. It has become a useful, attractive, and challenging research are...
ver más
|
|
|
|
|
|
|
|
|
|
|
Natalia Vanetik and Elisheva Mimoun
Toxic online content has become a major issue in recent years due to the exponential increase in the use of the internet. In France, there has been a significant increase in hate speech against migrant and Muslim communities following events such as Grea...
ver más
|
|
|
|
|
|
|
|
|
|
|
Harshkumar Mehta and Kalpdrum Passi
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 t...
ver más
|
|
|
|
|
|