Abstract
Often sentences of correct news are either made biased towards a particular person or a group of persons or parties or maybe distorted to add some sentiment or importance in it. Engaged readers often are not able to extract the inherent meaning of such synthetic sentences. In Bengali, the news contents of the synthetic sentences are presented in such a rich way that it usually becomes difficult to identify the synthetic part of it. We have used machine learning algorithms to classify Bengali news sentences into synthetic and legitimate and then used some rule-based postprocessing on each of these models. Finally, we have developed a voting based combination of these models to build a hybrid model for Bengali synthetic sentence identification. This is a new task and therefore we could not compare it with any existing work in the field. Identification of such types of sentences may be used to improve the performance of identifying fake news and satire news. Thus, identifying molecular level biasness in news articles.- Anthology ID:
- 2019.icon-1.23
- Volume:
- Proceedings of the 16th International Conference on Natural Language Processing
- Month:
- December
- Year:
- 2019
- Address:
- International Institute of Information Technology, Hyderabad, India
- Editors:
- Dipti Misra Sharma, Pushpak Bhattacharya
- Venue:
- ICON
- SIG:
- Publisher:
- NLP Association of India
- Note:
- Pages:
- 193–200
- Language:
- URL:
- https://aclanthology.org/2019.icon-1.23
- DOI:
- Cite (ACL):
- Soma Das and Sanjay Chatterji. 2019. Identification of Synthetic Sentence in Bengali News using Hybrid Approach. In Proceedings of the 16th International Conference on Natural Language Processing, pages 193–200, International Institute of Information Technology, Hyderabad, India. NLP Association of India.
- Cite (Informal):
- Identification of Synthetic Sentence in Bengali News using Hybrid Approach (Das & Chatterji, ICON 2019)
- PDF:
- https://preview.aclanthology.org/fix-dup-bibkey/2019.icon-1.23.pdf