Deep Learning Approach for Multi-Class Identification from Domestic Violence Online Posts

Deep Learning for Multi-Class Identification From Domestic Violence Online Posts involves training a neural network to recognize patterns and features in text that are indicative of domestic violence. The aim is to develop, train and evaluate a multiclass classification model on a dataset of online posts so that model can identify and classify domestic violence-related content from online posts. By conducting various analysis tests, models will predict accurately and distinguish between different types of domestic violence, in order to better understand the prevalence and specific forms of abuse occurring within online communities. The model will be trained on a dataset of online posts and will be evaluated on its ability to accurately classify new, unseen data. The audio, selected text, image and will be classified to display the results. The outcome of this project will be a deep learning model that can effectively identify and classify different forms of domestic violence in online posts.