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Improving international attractiveness of higher education institutions based on text mining and sentiment analysis

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Resumo:Purpose: The increasing competition among higher education institutions (HEI) has led students to conduct a more in-depth analysis to choose where to study abroad. Since students are usually unable to visit each HEIs before making their decision, they are strongly influenced by what is written by former international students (IS) on the internet. HEIs also benefit from such information online. The purpose of this paper is to provide an understanding of the drivers of HEIs success online. Design/methodology/approach: Due to the increasing amount of information published online, HEIs have to use automatic techniques to search for patterns instead of analysing such information manually. The present paper uses text mining (TM) and sentiment analysis (SA) to study online reviews of IS about their HEIs. The paper studied 1938 reviews from 65 different business schools with Association to Advance Collegiate Schools of Business accreditation. Findings: Results show that HEIs may become more attractive online if they financially support students cost of living, provide courses in English, and promote an international environment. Research limitations/implications: Despite the use of a major platform with a broad number of reviews from students around the world, other sources focussed on other types of HEIs may have been used to reinforce the findings in the current paper. Originality/value: The study pioneers the use of TM and SA to highlight topics and sentiments mentioned in online reviews by students attending HEIs, clarifying how such opinions are correlated with satisfaction. Using such information, HEIs’ managers may focus their efforts on promoting international attractiveness of their institutions.
Autores principais:Santos, Carolina Leana
Outros Autores:Rita, Paulo; Guerreiro, João
Assunto:Higher education International student mobility Sentiment analysis Text mining Topic modelling Education Organizational Behavior and Human Resource Management
Ano:2018
País:Portugal
Tipo de documento:artigo
Tipo de acesso:acesso aberto
Instituição associada:Universidade Nova de Lisboa
Idioma:inglês
Origem:Repositório Institucional da UNL
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author Santos, Carolina Leana
author2 Rita, Paulo
Guerreiro, João
author2_role author
author
author_facet Santos, Carolina Leana
Santos, Carolina Leana
Rita, Paulo
Guerreiro, João
Rita, Paulo
Guerreiro, João
author_role author
contributor_name_str_mv NOVA Information Management School (NOVA IMS)
Information Management Research Center (MagIC) - NOVA Information Management School
Associação Portuguesa para o Estudo do Quaternário (APEQ)
RUN
country_str PT
creators_json_str [{\"Person.name\":\"Santos, Carolina Leana\"},{\"Person.name\":\"Rita, Paulo\"},{\"Person.name\":\"Guerreiro, João\"}]
datacite.contributors.contributor.contributorName.fl_str_mv NOVA Information Management School (NOVA IMS)
Information Management Research Center (MagIC) - NOVA Information Management School
Associação Portuguesa para o Estudo do Quaternário (APEQ)
RUN
datacite.creators.creator.creatorName.fl_str_mv Santos, Carolina Leana
Rita, Paulo
Guerreiro, João
datacite.date.Accepted.fl_str_mv 2018-01-01T00:00:00Z
datacite.date.available.fl_str_mv 2022-12-07T22:06:17Z
datacite.date.embargoed.fl_str_mv 2022-12-07T22:06:17Z
datacite.rights.fl_str_mv http://purl.org/coar/access_right/c_abf2
datacite.subjects.subject.fl_str_mv Higher education
International student mobility
Sentiment analysis
Text mining
Topic modelling
Education
Organizational Behavior and Human Resource Management
datacite.titles.title.fl_str_mv Improving international attractiveness of higher education institutions based on text mining and sentiment analysis
dc.contributor.none.fl_str_mv NOVA Information Management School (NOVA IMS)
Information Management Research Center (MagIC) - NOVA Information Management School
Associação Portuguesa para o Estudo do Quaternário (APEQ)
RUN
dc.creator.none.fl_str_mv Santos, Carolina Leana
Rita, Paulo
Guerreiro, João
dc.date.Accepted.fl_str_mv 2018-01-01T00:00:00Z
dc.date.available.fl_str_mv 2022-12-07T22:06:17Z
dc.date.embargoed.fl_str_mv 2022-12-07T22:06:17Z
dc.format.none.fl_str_mv application/pdf
dc.identifier.none.fl_str_mv http://hdl.handle.net/10362/146060
dc.language.none.fl_str_mv eng
dc.rights.none.fl_str_mv http://purl.org/coar/access_right/c_abf2
dc.subject.none.fl_str_mv Higher education
International student mobility
Sentiment analysis
Text mining
Topic modelling
Education
Organizational Behavior and Human Resource Management
dc.title.fl_str_mv Improving international attractiveness of higher education institutions based on text mining and sentiment analysis
dc.type.none.fl_str_mv http://purl.org/coar/resource_type/c_6501
description Purpose: The increasing competition among higher education institutions (HEI) has led students to conduct a more in-depth analysis to choose where to study abroad. Since students are usually unable to visit each HEIs before making their decision, they are strongly influenced by what is written by former international students (IS) on the internet. HEIs also benefit from such information online. The purpose of this paper is to provide an understanding of the drivers of HEIs success online. Design/methodology/approach: Due to the increasing amount of information published online, HEIs have to use automatic techniques to search for patterns instead of analysing such information manually. The present paper uses text mining (TM) and sentiment analysis (SA) to study online reviews of IS about their HEIs. The paper studied 1938 reviews from 65 different business schools with Association to Advance Collegiate Schools of Business accreditation. Findings: Results show that HEIs may become more attractive online if they financially support students cost of living, provide courses in English, and promote an international environment. Research limitations/implications: Despite the use of a major platform with a broad number of reviews from students around the world, other sources focussed on other types of HEIs may have been used to reinforce the findings in the current paper. Originality/value: The study pioneers the use of TM and SA to highlight topics and sentiments mentioned in online reviews by students attending HEIs, clarifying how such opinions are correlated with satisfaction. Using such information, HEIs’ managers may focus their efforts on promoting international attractiveness of their institutions.
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eu_rights_str_mv openAccess
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language eng
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organization_str_mv urn:organizationAcronym:unl
person_str_mv Santos, Carolina Leana
Rita, Paulo
Guerreiro, João
publishDate 2018
reponame_str Repositório Institucional da UNL
repository_id_str urn:repositoryAcronym:run
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spelling engenPurpose: The increasing competition among higher education institutions (HEI) has led students to conduct a more in-depth analysis to choose where to study abroad. Since students are usually unable to visit each HEIs before making their decision, they are strongly influenced by what is written by former international students (IS) on the internet. HEIs also benefit from such information online. The purpose of this paper is to provide an understanding of the drivers of HEIs success online. Design/methodology/approach: Due to the increasing amount of information published online, HEIs have to use automatic techniques to search for patterns instead of analysing such information manually. The present paper uses text mining (TM) and sentiment analysis (SA) to study online reviews of IS about their HEIs. The paper studied 1938 reviews from 65 different business schools with Association to Advance Collegiate Schools of Business accreditation. Findings: Results show that HEIs may become more attractive online if they financially support students cost of living, provide courses in English, and promote an international environment. Research limitations/implications: Despite the use of a major platform with a broad number of reviews from students around the world, other sources focussed on other types of HEIs may have been used to reinforce the findings in the current paper. Originality/value: The study pioneers the use of TM and SA to highlight topics and sentiments mentioned in online reviews by students attending HEIs, clarifying how such opinions are correlated with satisfaction. Using such information, HEIs’ managers may focus their efforts on promoting international attractiveness of their institutions.application/pdfenImproving international attractiveness of higher education institutions based on text mining and sentiment analysisSantos, Carolina LeanaRita, PauloGuerreiro, JoãoNOVA Information Management School (NOVA IMS)Information Management Research Center (MagIC) - NOVA Information Management SchoolAssociação Portuguesa para o Estudo do Quaternário (APEQ)HostingInstitutionOrganizationalRUNe-mailmailto:run@unl.ptrun@unl.ptISSNIsPartOf0951-354XURNIsPartOfPURE: 5819082URNIsPartOfPURE UUID: c73c859c-eda4-4288-9e40-7ef6e2219e75URNIsPartOfScopus: 85045695822URNIsPartOfWOS: 000430192200007URNIsPartOfORCID: /0000-0001-6050-9958/work/151407766DOIIsPartOf10.1108/IJEM-01-2017-00272022-12-07T22:06:17Z2018-01-012018-01-01T00:00:00ZHandlehttp://hdl.handle.net/10362/146060http://purl.org/coar/access_right/c_abf2open accessHigher educationInternational student mobilitySentiment analysisText miningTopic modellingEducationOrganizational Behavior and Human Resource Management484584 bytesliteraturehttp://purl.org/coar/resource_type/c_6501journal articlehttp://purl.org/coar/access_right/c_abf2application/pdffulltexthttps://run.unl.pt/bitstreams/029e667e-42d9-4bcb-b984-58aaa0ad3b40/download
spellingShingle Improving international attractiveness of higher education institutions based on text mining and sentiment analysis
Improving international attractiveness of higher education institutions based on text mining and sentiment analysis
Santos, Carolina Leana
Higher education
International student mobility
Sentiment analysis
Text mining
Topic modelling
Education
Organizational Behavior and Human Resource Management
Santos, Carolina Leana
Higher education
International student mobility
Sentiment analysis
Text mining
Topic modelling
Education
Organizational Behavior and Human Resource Management
status NEW
subject.fl_str_mv Higher education
International student mobility
Sentiment analysis
Text mining
Topic modelling
Education
Organizational Behavior and Human Resource Management
title Improving international attractiveness of higher education institutions based on text mining and sentiment analysis
title_full Improving international attractiveness of higher education institutions based on text mining and sentiment analysis
title_fullStr Improving international attractiveness of higher education institutions based on text mining and sentiment analysis
Improving international attractiveness of higher education institutions based on text mining and sentiment analysis
title_full_unstemmed Improving international attractiveness of higher education institutions based on text mining and sentiment analysis
Improving international attractiveness of higher education institutions based on text mining and sentiment analysis
title_short Improving international attractiveness of higher education institutions based on text mining and sentiment analysis
title_sort Improving international attractiveness of higher education institutions based on text mining and sentiment analysis
topic Higher education
International student mobility
Sentiment analysis
Text mining
Topic modelling
Education
Organizational Behavior and Human Resource Management
topic_facet Higher education
International student mobility
Sentiment analysis
Text mining
Topic modelling
Education
Organizational Behavior and Human Resource Management
url http://hdl.handle.net/10362/146060
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