Published June 21, 2021
| Version 2
Journal article
Open
Hope Speech detection in under-resourced Kannada language
Authors/Creators
- 1. Indian Institute of Information Technology Tiruchirapalli
- 2. ULTRA Arts and Science College, Madurai Kamaraj University, Madurai, Tamil Nadu, India
- 3. Kongu Engineering College, Erode, Tamil Nadu, India
- 4. Sultan Idris Education University, Tanjong Malim, Perak, Malaysia
- 5. Mu Sigma Inc., Bangalore, Karnataka, India
- 6. Insight SFI Research Centre for Data Analytics, Data Science Institute, National University of Ireland Galway, Galway, Ireland
Description
@article{hande-etal-kanhope,
title = "Hope Speech detection in under-resourced Kannada language",
author = "Hande, Adeep and
Priyadharshini, Ruba and
Sampath, Anbukkarasi and
Thamburaj, Kingston Pal and
Chandran, Prabakaran and
Chakravarthi, Bharathi Raja ",
journal={SN Computer Science},
publisher={Springer}
}
Notes
Numerous methods have been developed to monitor the spread of negativity in modern years by eliminating vulgar, offensive, and fierce comments from social media platforms. However, there are relatively lesser amounts of study that converges on embracing positivity, reinforcing supportive and reassuring content in online forums. Consequently, we propose creating an English-Kannda Hope speech dataset, KanHope and comparing several experiments to provide benchmarking for the dataset. The dataset consists of 6,176 user-generated comments in code mixed Kannada crawled from YouTube and manually labelled as bearing hope speech or not-hope speech. In addition, we introduce DC-BERT4HOPE, a dual-channel model that uses the English translation of KanHopeEDI for additional training to promote hope speech detection. The approach achieves a weighted F1-score of 0.756, bettering other models. Henceforth, KanHope aims to instigate research in Kannada while broadly promoting researchers to take a pragmatic approach towards online content that encourages, positive, and supportive.