TY - GEN
T1 - NEHATE
T2 - 26th European Conference on Artificial Intelligence, ECAI 2023
AU - Thapa, Surendrabikram
AU - Rauniyar, Kritesh
AU - Shiwakoti, Shuvam
AU - Poudel, Sweta
AU - Naseem, Usman
AU - Nasim, Mehwish
N1 - Copyright the Author(s) 2023. Version archived for private and non-commercial use with the permission of the author/s and according to publisher conditions. For further rights please contact the publisher.
PY - 2023
Y1 - 2023
N2 - The use of social media during election campaigns has become increasingly popular. However, the unbridled nature of online discourse can lead to the propagation of hate speech, which has far-reaching implications for the democratic process. Natural Language Processing (NLP) techniques are being used to counteract the spread of hate speech and promote healthy online discourse. Despite the increasing need for NLP techniques to combat hate speech, research on low-resource languages such as Nepali is limited, posing a challenge to the realization of the United Nations' Leave No One Behind principle, which calls for inclusive development that benefits all individuals and communities, regardless of their backgrounds or circumstances. To bridge this gap, we introduce NEHATE, a large-scale manually annotated dataset of hate speech and its targets in Nepali local election discourse. The dataset comprises 13,505 tweets, annotated for hate speech with further sub-categorization of hate speech into targets such as community, individual, and organization. Benchmarking of the dataset with various algorithms has shown potential for performance improvement. We have made the dataset publicly available at https://github.com/shucoll/NEHate to promote further research and development, while also contributing to the UN SDGs aimed at fostering peaceful, inclusive societies, and justice and strong institutions.
AB - The use of social media during election campaigns has become increasingly popular. However, the unbridled nature of online discourse can lead to the propagation of hate speech, which has far-reaching implications for the democratic process. Natural Language Processing (NLP) techniques are being used to counteract the spread of hate speech and promote healthy online discourse. Despite the increasing need for NLP techniques to combat hate speech, research on low-resource languages such as Nepali is limited, posing a challenge to the realization of the United Nations' Leave No One Behind principle, which calls for inclusive development that benefits all individuals and communities, regardless of their backgrounds or circumstances. To bridge this gap, we introduce NEHATE, a large-scale manually annotated dataset of hate speech and its targets in Nepali local election discourse. The dataset comprises 13,505 tweets, annotated for hate speech with further sub-categorization of hate speech into targets such as community, individual, and organization. Benchmarking of the dataset with various algorithms has shown potential for performance improvement. We have made the dataset publicly available at https://github.com/shucoll/NEHate to promote further research and development, while also contributing to the UN SDGs aimed at fostering peaceful, inclusive societies, and justice and strong institutions.
UR - http://www.scopus.com/inward/record.url?scp=85175840433&partnerID=8YFLogxK
U2 - 10.3233/FAIA230535
DO - 10.3233/FAIA230535
M3 - Conference proceeding contribution
AN - SCOPUS:85175840433
SN - 9781643684369
T3 - Frontiers in Artificial Intelligence and Applications
SP - 2346
EP - 2353
BT - ECAI 2023
A2 - Gal, Kobi
A2 - Nowé, Ann
A2 - Nalepa, Grzegorz J.
A2 - Fairstein, Roy
A2 - Rădulescu, Roxana
PB - IOS Press
CY - Amsterdam
Y2 - 30 September 2023 through 4 October 2023
ER -