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Deductions from a Sub-Saharan African bank’s tweets: A sentiment analysis approach

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dc.title Deductions from a Sub-Saharan African bank’s tweets: A sentiment analysis approach en
dc.contributor.author Botchway, Raphael Kwaku
dc.contributor.author Jibril, Abdul Bashiru
dc.contributor.author Komínková Oplatková, Zuzana
dc.contributor.author Chovancová, Miloslava
dc.relation.ispartof Cogent Economics and Finance
dc.identifier.issn 2332-2039 Scopus Sources, Sherpa/RoMEO, JCR
dc.date.issued 2020
utb.relation.volume 8
utb.relation.issue 1
dc.type article
dc.language.iso en
dc.publisher Cogent OA
dc.identifier.doi 10.1080/23322039.2020.1776006
dc.relation.uri https://www.tandfonline.com/doi/full/10.1080/23322039.2020.1776006
dc.subject social media en
dc.subject twitter en
dc.subject tweet en
dc.subject sentiment analysis en
dc.subject VADER en
dc.subject Ecobank en
dc.subject Africa en
dc.description.abstract The upsurge in social media websites has in no doubt triggered a huge source of data for mining interesting expressions on a variety of subjects. These expressions on social media websites empower firms and individuals to discover varied interpretations regarding the opinions expressed. In Sub-Saharan Africa, financial institutions are making the needed technological investments required to remain competitive in today’s challenging global business environment. Twitter as one of the digital communication tools has in recent times been integrated into the marketing communication tools of banks to augment the free flow of information. In this light, the purpose of the present study is to perform a sentiment analysis on a large dataset of tweets associated with the Ecobank Group, a prominent pan-African bank in sub-Saharan Africa using four different sentiment lexicons to determine the best lexicon based on its performance. Our results show that Valence Aware Dictionary and sEntiment Reasoner (VADER) outperforms all the other three lexicons based on accuracy and computational efficiency. Additionally, we generated a word cloud to visually examine the terms in the positive and negative sentiment categories based on VADER. Our approach demonstrates that in today’s world of empowered customers, firms need to focus on customer engagement to enhance customer experience via social media channels (e.g., Twitter) since the meaning of competitive advantage has shifted from purely competing over price and product to building loyalty and trust. In theory, the study contributes to broadening the scope of online banking given the interplay of consumer sentiments via the social media channel. Limitations and future research directions are discussed at the end of the paper. © 2020, © 2020 The Author(s). This open access article is distributed under a Creative Commons Attribution (CC-BY) 4.0 license. en
utb.faculty Faculty of Applied Informatics
utb.faculty Faculty of Management and Economics
dc.identifier.uri http://hdl.handle.net/10563/1009774
utb.identifier.scopus 2-s2.0-85086780271
utb.identifier.wok 000615151000001
utb.source j-scopus
dc.date.accessioned 2020-07-10T13:51:21Z
dc.date.available 2020-07-10T13:51:21Z
dc.description.sponsorship Tomas Bata University in Zlin [IGA/CebiaTech/2020/001]
dc.rights Attribution 4.0 International
dc.rights.uri http://creativecommons.org/licenses/by/4.0/
dc.rights.access openAccess
utb.contributor.internalauthor Botchway, Raphael Kwaku
utb.contributor.internalauthor Jibril, Abdul Bashiru
utb.contributor.internalauthor Komínková Oplatková, Zuzana
utb.contributor.internalauthor Chovancová, Miloslava
utb.fulltext.affiliation Raphael Kwaku Botchway 1, Abdul Bashiru Jibril 2*, Zuzana Komínková Oplatková 1, Miloslava Chovancová 2 1 Faculty of Applied Informatics, Tomas Bata University in Zlin, Nam T.G. Masaryka 5555, Zlin 760 01, Czech Republic. 2 Faculty of Management and Economics, Tomas Bata University in Zlin, Nam T.G. Masaryka 5555, Zlin 760 01, Czech Republic. * Corresponding author: Abdul Bashiru Jibril, Faculty of Management and Economics, Tomas Bata University in Zlin, Zlin 760 01, Czech Republic E-mail: jibril@utb.cz; mallambash13@gmail.com
utb.fulltext.dates Published online: 08 Jun 2020
utb.fulltext.sponsorship This work was supported by the Internal Grant Agency of Tomas Bata University under the Projects no. IGA/CebiaTech/2020/001, IGA/FaME/2019/008 and IGA/FaME/2020/002. The work was further supported by the resources of A.I. Lab at the Faculty of Applied Informatics, Tomas Bata University in Zlin (ailab.fai.utb.cz). We are also thankful to the academic advice offered by Prof. Boris Popesko (Vice-dean for Research and Business Liaison) and Dr. Bedrich Zimola, all at the Faculty of Management and Economics of the above-mentioned University.
utb.wos.affiliation [Botchway, Raphael Kwaku; Oplatkova, Zuzana Kominkova] Tomas Bata Univ Zlin, Fac Appl Informat, Nam TG Masaryka 5555, Zlin 76001, Czech Republic; [Jibril, Abdul Bashiru; Chovancova, Miloslava] Tomas Bata Univ Zlin, Fac Econ & Management, Nam TG Masaryka 5555, Zlin 76001, Czech Republic
utb.scopus.affiliation Faculty of Applied Informatics, Tomas Bata University in Zlin, Nam T.G. Masaryka 5555, Zlin, 760 01, Czech Republic; Faculty of Management and Economics, Tomas Bata University in Zlin, Nam T.G. Masaryka 5555, Zlin, 760 01, Czech Republic
utb.fulltext.projects IGA/CebiaTech/2020/001
utb.fulltext.projects IGA/FaME/2019/008
utb.fulltext.projects IGA/FaME/2020/002
utb.fulltext.faculty Faculty of Applied Informatics
utb.fulltext.faculty Faculty of Management and Economics
utb.fulltext.faculty Faculty of Applied Informatics
utb.fulltext.faculty Faculty of Management and Economics
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Attribution 4.0 International Except where otherwise noted, this item's license is described as Attribution 4.0 International