Alvi, Quratulain, Ali, Syed Farooq, Ahmed, Sheikh Bilal, Khan, Nadeem Ahmad, Javed, Mazhar and Nobanee, Haitham 
ORCID: 0000-0003-4424-5600
(2023)
On the frontiers of Twitter data and sentiment analysis in election prediction: a review.
PEERJ COMPUTER SCIENCE, 9.
e1517-.
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Abstract
Election prediction using sentiment analysis is a rapidly growing field that utilizes natural language processing and machine learning techniques to predict the outcome of political elections by analyzing the sentiment of online conversations and news articles. Sentiment analysis, or opinion mining, involves using text analysis to identify and extract subjective information from text data sources. In the context of election prediction, sentiment analysis can be used to gauge public opinion and predict the likely winner of an election. Significant progress has been made in election prediction in the last two decades. Yet, it becomes easier to have its comprehensive view if it has been appropriately classified approach-wise, citation-wise, and technology-wise. The main objective of this article is to examine and consolidate the progress made in research about election prediction using Twitter data. The aim is to provide a comprehensive overview of the current state-of-the-art practices in this field while identifying potential avenues for further research and exploration.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | Sentiment Analsysi, Election prediction, Social media anlysis, Machine Learning, Policies, Classification, Social Media, Deep Learning, Twitter, Literature Review |
| Divisions: | Faculty of Humanities and Social Sciences > School of Histories, Languages and Cultures |
| Depositing User: | Symplectic Admin |
| Date Deposited: | 29 Nov 2023 16:28 |
| Last Modified: | 29 Nov 2023 16:28 |
| DOI: | 10.7717/peerj-cs.1517 |
| Open Access URL: | https://doi.org/10.7717/peerj-cs.1517 |
| Related URLs: | |
| URI: | https://livrepository.liverpool.ac.uk/id/eprint/3177072 |
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