Aggression Identification in Posts - two machine learning approaches
Year: 2020
Type: conference-paper
Abstract: Social media have changed the way people communicate. One of the aspects is cyber-aggression and interpersonal aggression that can be catalyzed by perceived anonymity. Automatically monitoring user-generated content in order to help moderating it is thus a hot topic. In this paper, we present and evaluate two supervised machine learning models to identify aggressive content and the level of aggressiveness. The first model uses random forest and linear regression while the second model uses deep learning techniques.
Source: HAL
Author: Ramiandrisoa, Faneva
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W4287863584