Abstract
Obtaining demand trends for products is an essential aspect of supply chain planning. It helps in generating scenarios for simulation before actual demands start pouring in. Presently, experts obtain this number manually from different News sources. In this paper, we have presented methods that can automate the information acquisition process. We have presented a joint framework that performs information extraction and sentiment analysis to acquire demand related information from business text documents. The proposed system leverages a TwinBERT-based deep neural network model to first extract product information for which demand is associated and then identify the respective sentiment polarity. The articles are also subjected to causal analytics, that, together yield rich contextual information about reasons for rise or fall of demand of various products. The enriched information is targeted for the decision-makers, analysts and knowledge workers. We have exhaustively evaluated our proposed models with datasets curated and annotated for two different domains namely, automobile sector and housing. The proposed model outperforms the existing baseline systems.- Anthology ID:
- 2024.wassa-1.21
- Volume:
- Proceedings of the 14th Workshop on Computational Approaches to Subjectivity, Sentiment, & Social Media Analysis
- Month:
- August
- Year:
- 2024
- Address:
- Bangkok, Thailand
- Editors:
- Orphée De Clercq, Valentin Barriere, Jeremy Barnes, Roman Klinger, João Sedoc, Shabnam Tafreshi
- Venues:
- WASSA | WS
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 264–272
- Language:
- URL:
- https://aclanthology.org/2024.wassa-1.21
- DOI:
- 10.18653/v1/2024.wassa-1.21
- Cite (ACL):
- Tirthankar Dasgupta and Manjira Sinha. 2024. Exploring Language Models to Analyze Market Demand Sentiments from News. In Proceedings of the 14th Workshop on Computational Approaches to Subjectivity, Sentiment, & Social Media Analysis, pages 264–272, Bangkok, Thailand. Association for Computational Linguistics.
- Cite (Informal):
- Exploring Language Models to Analyze Market Demand Sentiments from News (Dasgupta & Sinha, WASSA-WS 2024)
- PDF:
- https://preview.aclanthology.org/autopr/2024.wassa-1.21.pdf