Social Media and Sentimental Analysis: Central Bank of Nigeria Currency Redesign Policy

Author:

Oladapo Kayode Abiodun1,Akinbo Racheal Shade2

Affiliation:

1. McPherson University

2. Federal University of Technology

Abstract

Abstract

The identification and measurement of an online audience through the social media platform capitalise on the tonality of emotions on the social media presence. On October 20, the most populous country and acclaimed Africa’s largest economy, Nigeria announced the plans to redesign 200, 500 and 1000 banknotes in replacement of the existing ones. Nigerian citizens expressed different opinions over social media in support of or understanding of the proposed plan and process. Research has shown that shared sentiments on social media can influence the opinions of others and thus the Central Bank of Nigeria's currency redesign policy. This study, therefore, aimed to identify and analyse general sentiments towards the process of the currency redesign policy with the purpose of determining the citizen's attitude towards the policy, based on social media comments. Firstly, sentiment analysis was performed on naira redesign-related posts from a selected social media using lexicon-based and supervised machine learning techniques with the purpose of determining a summarised polarity percentage (i.e. negative or positive). The post was collected between January and February 2023. In addition, the performance of the lexicon-based classifier and seven machine learning-based classifiers was implemented and compared in order to use the best-performing classifier in determining the sentiment polarity of the post. Also, the thematic analysis on both positive and negative posts to further understand and revealed general views about the currency redesign policy. Finally, the analytical findings and the possibility of changing the currency redesign policy was discussed.

Publisher

Springer Science and Business Media LLC

Reference77 articles.

1. Adoma, A. F., Henry, N. M., & Chen, W. (2020). Comparative Analyses of Bert, Roberta, Distilbert, and Xlnet for Text-Based Emotion Recognition. 2020 17th International Computer Conference on Wavelet Active Media Technology and Information Processing (ICCWAMTIP). https://doi.org/10.1109/iccwamtip51612.2020.9317379

2. Adames I. (2022, September 6). 5 Types of Social Media Networks and The Benefits of Each One: Discover the latest trends in social media and learn how you can apply them to your business. https://www.searchenginejournal.com/social-media-networks-types/463203/.

3. Challenges and Prospects of social media on Digital Natives: The Case of Nigeria;Agbawe M;Journal of information and knowledge management,2018

4. An information-theoretic perspective of tf–idf measures;Aizawa A;Information Processing & Management,2003

5. A reliable sentiment analysis for classification of tweets in social networks;AminiMotlagh M;Social Network Analysis and Mining,2022

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3