Reading behind the tweets: A sentiment Clustering Approach
- Title
- Reading behind the tweets: A sentiment Clustering Approach
- Creator
- Saxena A.; Bhagat V.; Mahajan J.
- Description
- Market sentiment influence crude oil future prices in direct or indirect way. In order to measure the polarity of market sentiment various techniques has been deployed by industry and academia alike. This pilot study successfully introduced two instruments, namely topic modeling and Sentiment clustering, to unearth the prevailing sentiments behind crude oil future pricesThree main conclusions that can be drawn from empirical results are. First, the K-Means clustering algorithm is an effective technique for sentiment clustering compared to Louveian and MDS clustering techniques. Second sentiment polarity-related positive sentiments have shown more variations in comparison to neutral and negative sentiments. Third It is possible to extract the keywords related to essential factors influencing crude oil prices using the LDA technique under topic modeling 2022 IEEE.
- Source
- 2022 International Conference on Advanced Computing Technologies and Applications, ICACTA 2022
- Date
- 2022-01-01
- Publisher
- Institute of Electrical and Electronics Engineers Inc.
- Subject
- Crude oil; prices; sentiment analysis; topic modeling; tweets
- Coverage
- Saxena A., Christ University, India; Bhagat V., Christ University, India; Mahajan J., Christ University, India
- Rights
- Restricted Access
- Relation
- ISBN: 978-166549515-8
- Format
- Online
- Language
- English
- Type
- Conference paper
Collection
Citation
Saxena A.; Bhagat V.; Mahajan J., “Reading behind the tweets: A sentiment Clustering Approach,” CHRIST (Deemed To Be University) Institutional Repository, accessed February 24, 2025, https://archives.christuniversity.in/items/show/20437.