Cyberbullying
Linguistic Challenges in the Detection of Digital Violence in Latin America and the Caribbean
Promoting inclusive digital security through artificial intelligence powered detection
This research addresses cyberbullying detection on Twitter, focusing on Peruvian Spanish, by creating a dataset and comparing four machine-learning models. With a comprehensive approach, it seeks to overcome the lack of studies focused on the linguistic particularities of Latin America and the Caribbean. Its objective is to provide results that contribute to developing more effective strategies to combat cyberbullying in the region.
A Comparison of Classification Models to Detect Cyberbullying in the Peruvian Spanish Language on Twitter
This study compares four machine-learning models for cyberbullying detection on Twitter, specifically focusing on Peruvian Spanish. It uses a specially designed dataset for training these models and presents detailed results on each model's performance and ability to identify cyberbullying.
Manual: Creation and Validation of a Dataset for the Detection Cyberbullying in the Peruvian Spanish Language
This manual addresses the linguistic challenges associated with creating data to address social problems in the digital environment of the region, particularly in Peruvian Spanish. It describes in detail the process of creating and validating a specific dataset for this task, facing the complexities of the regional language. In addition, it provides a thorough explanation of data pre-processing using natural language processing techniques to improve detection efficiency.
