Studies Towards Language Independent Fake News Detection

Soumayan Majumder, Dipankar Das


Abstract
We have studied that fake news is currently one of the trending topic and it causes problem to many people and organization. We use COVID19 domain and 7 languages to work on. We collect our data from twitter. We build two types of model one is language dependent and other one is language independent. We get better result in language independent model for English, Hindi and Bengali language. Results of European languages like German, Italian, French and Spanish are comparable in both language dependent and independent model.
Anthology ID:
2021.icon-main.53
Volume:
Proceedings of the 18th International Conference on Natural Language Processing (ICON)
Month:
December
Year:
2021
Address:
National Institute of Technology Silchar, Silchar, India
Editors:
Sivaji Bandyopadhyay, Sobha Lalitha Devi, Pushpak Bhattacharyya
Venue:
ICON
SIG:
Publisher:
NLP Association of India (NLPAI)
Note:
Pages:
439–446
Language:
URL:
https://aclanthology.org/2021.icon-main.53
DOI:
Bibkey:
Cite (ACL):
Soumayan Majumder and Dipankar Das. 2021. Studies Towards Language Independent Fake News Detection. In Proceedings of the 18th International Conference on Natural Language Processing (ICON), pages 439–446, National Institute of Technology Silchar, Silchar, India. NLP Association of India (NLPAI).
Cite (Informal):
Studies Towards Language Independent Fake News Detection (Majumder & Das, ICON 2021)
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PDF:
https://aclanthology.org/2021.icon-main.53.pdf