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A review of social media posts from Unicredit bank in Europe: A sentiment analysis approach

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dc.title A review of social media posts from Unicredit bank in Europe: A sentiment analysis approach en
dc.contributor.author Botchway, Raphael Kwaku
dc.contributor.author Jibril, Abdul Bashiru
dc.contributor.author Kwarteng, Michael Adu
dc.contributor.author Chovancová, Miloslava
dc.contributor.author Komínková Oplatková, Zuzana
dc.relation.ispartof ACM International Conference Proceeding Series
dc.identifier.isbn 978-1-4503-7232-9
dc.date.issued 2019
dc.citation.spage 74
dc.citation.epage 79
dc.event.title 3rd International Conference on Business and Information Management, ICBIM 2019
dc.event.location Paris
utb.event.state-en France
utb.event.state-cs Francie
dc.event.sdate 2019-09-12
dc.event.edate 2019-09-14
dc.type conferenceObject
dc.language.iso en
dc.publisher Association for Computing Machinery
dc.identifier.doi 10.1145/3361785.3361814
dc.relation.uri https://dl.acm.org/doi/10.1145/3361785.3361814
dc.subject sentiment analysis en
dc.subject social media en
dc.subject tweet en
dc.subject Twitter en
dc.subject VADER en
dc.description.abstract In recent times, the increasing popularity of social media websites has provided a major source of data for mining public opinion on a variety of subjects. The opinions expressed on social media enables firms to discover individual perceived strengths and weaknesses regarding their operations as well as the products/services they offer. Twitter is one platform that gives us the opportunity to evaluate the opinions expressed by users. In this study, a dataset of tweets is downloaded from the official twitter account associated with UniCredit bank‟s main public relations outfit within the European sub-region using the Twitter API. Valence Aware Dictionary and sEntiment Reasoner (VADER), a lexicon and rule-based sentiment analysis tool that is specifically attuned to sentiments expressed on social media (e.g. Twitter), was used in conducting sentiment analysis on the tweets to examine the attitudes and feelings expressed. Using VADER to conduct sentiment analysis showed that the overall discussion was positive focusing on tweets describing UniCredit‟s engagement in corporate social responsibility activities, support for small and medium scale enterprises and business innovation. Our approach will enable the bank to gain insights on how to shape their online presence and address customer and stakeholder expectations. In theory, the study adds up to broaden the scope of online banking given the interplay of consumer sentiments via the social media channel. © 2019 Association for Computing Machinery. en
utb.faculty Faculty of Applied Informatics
utb.faculty Faculty of Management and Economics
dc.identifier.uri http://hdl.handle.net/10563/1009627
utb.identifier.obdid 43881212
utb.identifier.scopus 2-s2.0-85081686647
utb.source d-scopus
dc.date.accessioned 2020-04-03T15:08:54Z
dc.date.available 2020-04-03T15:08:54Z
utb.ou CEBIA-Tech
utb.contributor.internalauthor Botchway, Raphael Kwaku
utb.contributor.internalauthor Jibril, Abdul Bashiru
utb.contributor.internalauthor Kwarteng, Michael Adu
utb.contributor.internalauthor Chovancová, Miloslava
utb.contributor.internalauthor Komínková Oplatková, Zuzana
utb.fulltext.affiliation Raphael Kwaku Botchway, Abdul Bashiru Jibril, Michael Adu Kwarteng, Miloslava Chovancova, Zuzana Komínková Oplatková Tomas Bata University in Zlin, Zlin, Czech Republic Tomas Bata University in Zlin, Zlin, Czech Republic Tomas Bata University in Zlin, Zlin, Czech Republic Tomas Bata University in Zlin, Zlin, Czech Republic Tomas Bata University in Zlin, Zlin, Czech Republic
utb.fulltext.dates -
utb.fulltext.sponsorship This work was supported by the Ministry of Education, Youth and Sports of the Czech Republic within the National Sustainability Programme Project no. LO1303 (MSMT-7778/2014), further by the European Regional Development Fund under the Project CEBIA-Tech no. CZ.1.05/2.1.00/03.0089 and by Internal Grant Agency of Tomas Bata University under the Projects no. IGA/CebiaTech/2019/002 and IGA/FaME/2019/008. The work was further supported by resources of A.I. Lab at the Faculty of Applied Informatics, Tomas Bata University in Zlin (ailab.fai.utb.cz).
utb.scopus.affiliation Tomas Bata University in Zlin, Faculty of Applied Informatics, Nam T.G. Masaryka 5555, Zlin, 760 01, Czech Republic; Tomas Bata University in Zlin, Faculty of Management and Economics, Nam T.G. Masaryka 5555, Zlin, 760 01, Czech Republic
utb.fulltext.projects LO1303
utb.fulltext.projects MSMT-7778/2014
utb.fulltext.projects CZ.1.05/2.1.00/03.0089
utb.fulltext.projects IGA/CebiaTech/2019/002
utb.fulltext.projects IGA/FaME/2019/008
utb.identifier.jel -
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