CURAJ_IIITDWD@LT-EDI-ACL 2022: Hope Speech Detection in English YouTube Comments using Deep Learning Techniques
Year: 2022
Type: conference-paper
Abstract: Hope Speech are positive terms that help to promote or criticise a point of view without hurting the user's or community's feelings.Non-Hope Speech, on the other side, includes expressions that are harsh, ridiculing, or demotivating.The goal of this article is to find the hope speech comments in a YouTube dataset.The datasets were created as part of the "LT-EDI-ACL 2022: Hope Speech Detection for Equality, Diversity, and Inclusion" shared task.The shared task dataset was proposed in Malayalam, Tamil, English, Spanish, and Kannada languages.In this paper, we worked at English-language YouTube comments.We employed several deep learning based models such as DNN (dense or fully connected neural network), CNN (Convolutional Neural Network), Bi-LSTM (Bidirectional Long Short Term Memory Network), and GRU(Gated Recurrent Unit) to identify the hopeful comments.We also used Stacked LSTM-CNN and Stacked LSTM-LSTM network to train the model.The best macro avg F1-score 0.67 for development dataset was obtained using the DNN model.The macro avg F1-score of 0.67 was achieved for the classification done on the test data as well.
Authors: Vanshita Jha, Ankit Mishra, Sunil Saumya
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W4285184053