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Leveraging fine-grained sentiment analysis for competitivity

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dc.title Leveraging fine-grained sentiment analysis for competitivity en Nabareseh, Stephan Afful-Dadzie, Eric Klímek, Petr
dc.relation.ispartof Journal of Information and Knowledge Management
dc.identifier.issn 0219-6492 OCLC, Ulrich, Sherpa/RoMEO, JCR 2018
utb.relation.volume 17
utb.relation.issue 2
dc.type article
dc.language.iso en
dc.publisher World Scientific Publishing Co. Pte. Ltd.
dc.identifier.doi 10.1142/S0219649218500181
dc.subject Social media en
dc.subject telecommunication companies en
dc.subject sentiment analysis en
dc.subject facebook: twitter en
dc.subject competitive analysis en
dc.description.abstract The surge in the use of social media tools by most businesses and corporate society for varied purposes cannot be over emphasised. The two top social media sites heavily patronised by businesses are Facebook and Twitter. For companies to harness the business potential of social media to increase competitive advantage, sentiments behind textual data of their customers, fans and competitors must be monitored and analysed with keen interest. This paper demonstrates how companies in the Telecommunication industry can understand consumer opinions, frustrations and satisfaction through opinion mining analyses and interpret customers' textual data to enhance competitiveness. Sentiment analysis that classifies positive, negative and neutral sentiments of customers of the top three telecommunication companies in Ghana (MTN, Vodafone and Tigo) is studied. The proposed method extracts "intelligence" from the classified customers' comments and compares it with responses from the companies. The results show how customer sentiments can be harnessed into successful online advertising projects. Companies can use the results to enhance their responsiveness to customer-centred, improve on the quality of their service, integrate social sentiments into PR plan, develop a strategy for social media marketing and leverage on the advantages of online advertising. © 2018 World Scientific Publishing Co. en
utb.faculty Faculty of Management and Economics
utb.identifier.obdid 43878355
utb.identifier.scopus 2-s2.0-85044767396
utb.identifier.wok 000434477400007
utb.source j-scopus 2018-07-27T08:47:35Z 2018-07-27T08:47:35Z
dc.description.sponsorship Internal Grant Agency of Tomas Bata University [IGA/FaME/2016/019]
utb.contributor.internalauthor Nabareseh, Stephan
utb.contributor.internalauthor Klímek, Petr
utb.fulltext.affiliation Stephen Nabareseh*,†,§, Eric A®ul-Dadzie‡ and Petr Klimek* *Faculty of Management and Economics Tomas Bata University in Zlin, Czech Republic † Ghana Revenue Authority, Accra, Ghana ‡ University of Ghana Business School University of Ghana, Legon, Ghana §
utb.fulltext.dates Published 4 April 2018
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utb.fulltext.sponsorship This work was supported by Internal Grant Agency of Tomas Bata University under the project Nos. IGA/FaME/2016/019.
utb.wos.affiliation [Nabareseh, Stephen; Klimek, Petr] Tomas Bata Univ, Fac Econ & Management, Zlin, Czech Republic; [Nabareseh, Stephen] Ghana Revenue Author, Accra, Ghana; [Affuul-Dadzie, Eric] Univ Ghana, Sch Business, Legon, Ghana
utb.fulltext.projects IGA/FaME/2016/019
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