On the frontiers of Twitter data and sentiment analysis in election prediction: a review
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,...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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PeerJ Inc.
2023-08-01
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| Series: | PeerJ Computer Science |
| Subjects: | |
| Online Access: | https://peerj.com/articles/cs-1517.pdf |
| _version_ | 1797738318843084800 |
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| author | Quratulain Alvi Syed Farooq Ali Sheikh Bilal Ahmed Nadeem Ahmad Khan Mazhar Javed Haitham Nobanee |
| author_facet | Quratulain Alvi Syed Farooq Ali Sheikh Bilal Ahmed Nadeem Ahmad Khan Mazhar Javed Haitham Nobanee |
| author_sort | Quratulain Alvi |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-03-12T13:41:07Z |
| format | Article |
| id | doaj.art-537a3a42090745a8bfe8a728f2443120 |
| institution | Directory Open Access Journal |
| issn | 2376-5992 |
| language | English |
| last_indexed | 2024-03-12T13:41:07Z |
| publishDate | 2023-08-01 |
| publisher | PeerJ Inc. |
| record_format | Article |
| series | PeerJ Computer Science |
| spelling | doaj.art-537a3a42090745a8bfe8a728f24431202023-08-23T15:05:11ZengPeerJ Inc.PeerJ Computer Science2376-59922023-08-019e151710.7717/peerj-cs.1517On the frontiers of Twitter data and sentiment analysis in election prediction: a reviewQuratulain Alvi0Syed Farooq Ali1Sheikh Bilal Ahmed2Nadeem Ahmad Khan3Mazhar Javed4Haitham Nobanee5Department of Software Engineering, University of Management and Technology, Lahore, Punjab, PakistanDepartment of Software Engineering, University of Management and Technology, Lahore, Punjab, PakistanDepartment of Software Engineering, University of Management and Technology, Lahore, Punjab, PakistanSyed Babar Ali School of Science and Engineering, Lahore University of Management Sciences, Lahore, Punjab, PakistanDepartment of Software Engineering, University of Management and Technology, Lahore, Punjab, PakistanFaculty of Humanities and Social Sciences, University of Liverpool, Liverpool, United KingdomElection 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.https://peerj.com/articles/cs-1517.pdfSentiment AnalsysiElection predictionSocial media anlysisMachine LearningPoliciesClassification |
| spellingShingle | Quratulain Alvi Syed Farooq Ali Sheikh Bilal Ahmed Nadeem Ahmad Khan Mazhar Javed Haitham Nobanee On the frontiers of Twitter data and sentiment analysis in election prediction: a review PeerJ Computer Science Sentiment Analsysi Election prediction Social media anlysis Machine Learning Policies Classification |
| title | On the frontiers of Twitter data and sentiment analysis in election prediction: a review |
| title_full | On the frontiers of Twitter data and sentiment analysis in election prediction: a review |
| title_fullStr | On the frontiers of Twitter data and sentiment analysis in election prediction: a review |
| title_full_unstemmed | On the frontiers of Twitter data and sentiment analysis in election prediction: a review |
| title_short | On the frontiers of Twitter data and sentiment analysis in election prediction: a review |
| title_sort | on the frontiers of twitter data and sentiment analysis in election prediction a review |
| topic | Sentiment Analsysi Election prediction Social media anlysis Machine Learning Policies Classification |
| url | https://peerj.com/articles/cs-1517.pdf |
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