An Innovative Method for Election Prediction using Hybrid A-BiCNN-RNN Approach
- Title
- An Innovative Method for Election Prediction using Hybrid A-BiCNN-RNN Approach
- Creator
- Acharjee P.B.; Magadum A.A.; Thejovathi M.; Jain R.; Umarani K.; Nishant N.
- Description
- Sentiment, volumetric, and social network analyses, as well as other methods, are examined for their ability to predict key outcomes using data collected from social media. Different points of view are essential for making significant discoveries. Social media have been used by individuals all over the world to communicate and share ideas for decades. Sentiment analysis, often known as opinion mining, is a technique used to glean insights about how the public feels and thinks. By gauging how people feel about a candidate on social media, they can utilize sentiment analysis to predict who will win an upcoming election. There are three main steps in the proposed approach, and they are preprocessing, feature extraction, and model training. Negation handling often requires preprocessing. Natural Language Processing makes use of feature extraction. Following the feature selection process, the models are trained using BiCNN-RNN. The proposed method is superiorto the widely usedBiCNN and RNN methods. 2023 IEEE.
- Source
- 2nd International Conference on Automation, Computing and Renewable Systems, ICACRS 2023 - Proceedings, pp. 765-770.
- Date
- 2023-01-01
- Publisher
- Institute of Electrical and Electronics Engineers Inc.
- Subject
- Convolutional Neural Network (CNN); Election prediction; Natural Language Processing (NLP)
- Coverage
- Acharjee P.B., CHRIST University, Pune, India; Magadum A.A., Department of MCA, MIT-ADT University, Maharastra, Pune, India; Thejovathi M., Department of Computer Science and Engineering, Acharya Nagarjuna University, Guntur, India; Jain R., School of Arts & Humanities, IIMT University, Meerut, India; Umarani K., School of Arts & Humanities, IIMT University, Meerut, India; Nishant N., Department of Computer Science and Engineering, School of Engineering, Babu Banarasi Das University, Lucknow, India
- Rights
- Restricted Access
- Relation
- ISBN: 979-835034023-5
- Format
- Online
- Language
- English
- Type
- Conference paper
Collection
Citation
Acharjee P.B.; Magadum A.A.; Thejovathi M.; Jain R.; Umarani K.; Nishant N., “An Innovative Method for Election Prediction using Hybrid A-BiCNN-RNN Approach,” CHRIST (Deemed To Be University) Institutional Repository, accessed February 24, 2025, https://archives.christuniversity.in/items/show/19679.