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

Bibliographic Details
Main Author: Santos, Carolina Leana
Publication Date: 2018
Other Authors: Rita, Paulo, Guerreiro, João
Format: Article
Language: eng
Source: Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
Download full: http://hdl.handle.net/10362/146060
Summary: Santos, C. L., Rita, P., & Guerreiro, J. (2018). Improving international attractiveness of higher education institutions based on text mining and sentiment analysis. International Journal of Educational Management, 32(3), 431-447. DOI: 10.1108/IJEM-01-2017-0027
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spelling Improving international attractiveness of higher education institutions based on text mining and sentiment analysisHigher educationInternational student mobilitySentiment analysisText miningTopic modellingEducationOrganizational Behavior and Human Resource ManagementSantos, C. L., Rita, P., & Guerreiro, J. (2018). Improving international attractiveness of higher education institutions based on text mining and sentiment analysis. International Journal of Educational Management, 32(3), 431-447. DOI: 10.1108/IJEM-01-2017-0027Purpose: 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.NOVA Information Management School (NOVA IMS)Information Management Research Center (MagIC) - NOVA Information Management SchoolRUNSantos, Carolina LeanaRita, PauloGuerreiro, João2022-12-07T22:06:17Z2018-01-012018-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article17application/pdfhttp://hdl.handle.net/10362/146060eng0951-354XPURE: 5819082https://doi.org/10.1108/IJEM-01-2017-0027info:eu-repo/semantics/openAccessreponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiainstacron:RCAAP2024-05-22T18:07:13Zoai:run.unl.pt:10362/146060Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireinfo@rcaap.ptopendoar:https://opendoar.ac.uk/repository/71602025-05-28T17:37:33.332641Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiafalse
dc.title.none.fl_str_mv Improving international attractiveness of higher education institutions based on text mining and sentiment analysis
title Improving international attractiveness of higher education institutions based on text mining and sentiment analysis
spellingShingle 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
title_short 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
title_full_unstemmed 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
author Santos, Carolina Leana
author_facet Santos, Carolina Leana
Rita, Paulo
Guerreiro, João
author_role author
author2 Rita, Paulo
Guerreiro, João
author2_role author
author
dc.contributor.none.fl_str_mv NOVA Information Management School (NOVA IMS)
Information Management Research Center (MagIC) - NOVA Information Management School
RUN
dc.contributor.author.fl_str_mv Santos, Carolina Leana
Rita, Paulo
Guerreiro, João
dc.subject.por.fl_str_mv Higher education
International student mobility
Sentiment analysis
Text mining
Topic modelling
Education
Organizational Behavior and Human Resource Management
topic Higher education
International student mobility
Sentiment analysis
Text mining
Topic modelling
Education
Organizational Behavior and Human Resource Management
description Santos, C. L., Rita, P., & Guerreiro, J. (2018). Improving international attractiveness of higher education institutions based on text mining and sentiment analysis. International Journal of Educational Management, 32(3), 431-447. DOI: 10.1108/IJEM-01-2017-0027
publishDate 2018
dc.date.none.fl_str_mv 2018-01-01
2018-01-01T00:00:00Z
2022-12-07T22:06:17Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/10362/146060
url http://hdl.handle.net/10362/146060
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 0951-354X
PURE: 5819082
https://doi.org/10.1108/IJEM-01-2017-0027
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv 17
application/pdf
dc.source.none.fl_str_mv reponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
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reponame_str Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
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repository.name.fl_str_mv Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
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