Twitter corpus of Resource-Scarce Languages for Sentiment Analysis and Multilingual Emoji Prediction
Nurendra Choudhary, Rajat Singh, Vijjini Anvesh Rao, Manish Shrivastava
Abstract
In this paper, we leverage social media platforms such as twitter for developing corpus across multiple languages. The corpus creation methodology is applicable for resource-scarce languages provided the speakers of that particular language are active users on social media platforms. We present an approach to extract social media microblogs such as tweets (Twitter). In this paper, we create corpus for multilingual sentiment analysis and emoji prediction in Hindi, Bengali and Telugu. Further, we perform and analyze multiple NLP tasks utilizing the corpus to get interesting observations.- Anthology ID:
- C18-1133
- Volume:
- Proceedings of the 27th International Conference on Computational Linguistics
- Month:
- August
- Year:
- 2018
- Address:
- Santa Fe, New Mexico, USA
- Editors:
- Emily M. Bender, Leon Derczynski, Pierre Isabelle
- Venue:
- COLING
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 1570–1577
- Language:
- URL:
- https://aclanthology.org/C18-1133
- DOI:
- Cite (ACL):
- Nurendra Choudhary, Rajat Singh, Vijjini Anvesh Rao, and Manish Shrivastava. 2018. Twitter corpus of Resource-Scarce Languages for Sentiment Analysis and Multilingual Emoji Prediction. In Proceedings of the 27th International Conference on Computational Linguistics, pages 1570–1577, Santa Fe, New Mexico, USA. Association for Computational Linguistics.
- Cite (Informal):
- Twitter corpus of Resource-Scarce Languages for Sentiment Analysis and Multilingual Emoji Prediction (Choudhary et al., COLING 2018)
- PDF:
- https://preview.aclanthology.org/ingest-2024-clasp/C18-1133.pdf