A comprehensive cross-language framework for harmful content detection with the aid of sentiment analysis

arXiv:2403.01270v1 Announce Type: new
Abstract: In today's digital world, social media plays a significant role in facilitating communication and content sharing. However, the exponential rise in user-generated content has led to challenges in maintaining a respectful online environment. In some cases, users have taken advantage of anonymity in order to use harmful language, which can negatively affect the user experience and pose serious social problems. Recognizing the limitations of manual moderation, automatic detection systems have been developed to tackle this …

abstract analysis arxiv cases challenges communication cs.cl detection digital digital world environment framework generated language media role sentiment sentiment analysis social social media type world