Sentiment analysis of political discussion on Twitter in Nigeria's 2019 presidential election
Bibliographic Data
| ID | 21784785 |
|---|---|
| Authors | Aderonke A Oni (0000-0002-8625-2748, Covenant University), Samuel Oni (0000-0003-3513-0844, Covenant University), Blessing E Udemezue (Covenant University) |
| Year | 2021 |
| Volume | 13 |
| Issue | 4 |
| Pages | 462 |
| Publication date | 2021-01-01 |
| Open Access | No |
| Type | ARTICLE |
| Venue | International Journal of Electronic Governance (JOURNAL) |
| Journal identifiers | ISSN: 1742-7517 • E-ISSN: 1742-7509 |
| Publisher | Inderscience Publishers (PUBLISHER • GB) |
| DOI | 10.1504/ijeg.2021.121241 |
| OpenAlex | W4214810516 |
| Language | EN |
Social media have helped in political communication by reinforcing social change and commitments from governments. This study analyses political discussion on Twitter during the 2019 Nigeria general election. The aim is to identify popular issues discussed and opinion of citizens on popular presidential candidates' social media network and correlate the online discussion with real world events during the 2019 election. Five most popular presidential candidates were selected for the investigation. Latent Dirichlet allocation (LDA) model was used to identify frequent terms and topics discussed. Sentiment of the tweets was analysed using National Research Council Canada (NRC) Emotion Lexicon. Findings revealed that Twitter is mainly used for political discussion that cantered on personal representation, political party's promotion and elections matters. The behaviour of users shows that Twitter platform is not being used to share original political ideologies, instead the platform was used for re-tweeting of tweets and political campaigns for candidates
General election · Ideology · Lexicon · Media studies · Political communication · Political science · Politics · Presidential election · Presidential system · Public relations · Sentiment analysis · Social media · Sociology · Computer Science · Hate Speech and Cyberbullying Detection · Law · Sentiment Analysis and Opinion Mining · Social Media and Politics · Artificial Intelligence
| Highly cited | No |
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