Airline Twitter Sentiment Classification using Deep Learning Fusion
- Title
- Airline Twitter Sentiment Classification using Deep Learning Fusion
- Creator
- Lakshmanarao A.; Gupta C.; Kiran T.S.R.
- Description
- Since the advent of the Internet, the way people express their ideas and beliefs has undergone significant transformation. Blogs, online forums, product review websites and social media are increasingly the primary means of distributing information about new products. Twitter, in particular, is giving people a platform to air their views and opinions about a variety of events and products. In order to continually enhance the quantity and quality of their products and services, entrepreneurs constantly need input from their customers. Businesses are always looking for ways to increase the quality of their products and services. As a result, it's tough to understand the consumer's sentiments because of the large volume of data. In this research work, a Kaggle dataset of airline tweets for sentiment analysis was used. The dataset contains 11,540 reviews. We proposed an ensemble CNN, LSTM architecture for sentiment analysis. For comparison of the proposed system, LSTM alone also tested for similar dataset. LSTM was given an accuracy of 91% and the proposed ensemble framework with LSTM and CNN was given an accuracy of 93%. The experiments showed that the proposed model achieved better accuracy when compared to conventional techniques. 2022 IEEE.
- Source
- 2022 International Conference on Smart Generation Computing, Communication and Networking, SMART GENCON 2022
- Date
- 2022-01-01
- Publisher
- Institute of Electrical and Electronics Engineers Inc.
- Subject
- Airline Tweets; CNN; Kaggle; LSTM
- Coverage
- Lakshmanarao A., Aditya Engineering College, Department of Information Technology, Surampalem, India; Gupta C., Christ University, School of Commerce, Finance and Accountancy, India; Kiran T.S.R., P.B. S College of Arts & Science, Department of Computer Science, A.P, Vijayawada, India
- Rights
- Restricted Access
- Relation
- ISBN: 978-166545499-5
- Format
- Online
- Language
- English
- Type
- Conference paper
Collection
Citation
Lakshmanarao A.; Gupta C.; Kiran T.S.R., “Airline Twitter Sentiment Classification using Deep Learning Fusion,” CHRIST (Deemed To Be University) Institutional Repository, accessed February 27, 2025, https://archives.christuniversity.in/items/show/20100.