A text mining and topic modelling perspective of ethnic marketing research
Autor(a) principal: | |
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Data de Publicação: | 2019 |
Outros Autores: | , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | http://hdl.handle.net/10071/17467 |
Resumo: | This study presents an enhanced automated approach based on literature analysis and synthesis for establishing the dimensions of the ethnic marketing literature, covering a set of 239 journal articles published by nine major publishers. The approach reported is enhanced by two novel procedures to address previously identified limitations, namely: definition of a relevant dictionary based on both a sufficient lexicon extracted from a definition of the core theme and a conditional dictionary, with related but non-core terms; and a visually appealing pictorial representation to summarize the discovered topics. The application of the method to ethnic marketing indicates that ethnic marketing research is characterized by high conceptual heterogeneity, although a clear definition of “ethnic marketing” is imperative for research development. Overall, the paper advances an approach with considerable scalability advantages when compared with extant approaches, an important issue to consider when textual sources become big data. |
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A text mining and topic modelling perspective of ethnic marketing researchEthnic marketingFiltering dictionariesLiterature analysis and synthesisLiterature dimensionsText miningTopic modellingThis study presents an enhanced automated approach based on literature analysis and synthesis for establishing the dimensions of the ethnic marketing literature, covering a set of 239 journal articles published by nine major publishers. The approach reported is enhanced by two novel procedures to address previously identified limitations, namely: definition of a relevant dictionary based on both a sufficient lexicon extracted from a definition of the core theme and a conditional dictionary, with related but non-core terms; and a visually appealing pictorial representation to summarize the discovered topics. The application of the method to ethnic marketing indicates that ethnic marketing research is characterized by high conceptual heterogeneity, although a clear definition of “ethnic marketing” is imperative for research development. Overall, the paper advances an approach with considerable scalability advantages when compared with extant approaches, an important issue to consider when textual sources become big data.Elsevier2019-02-28T17:00:26Z2020-02-07T00:00:00Z2019-01-01T00:00:00Z20192019-02-28T16:59:45+0000info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10071/17467eng0148-296310.1016/j.jbusres.2019.01.053Moro, S.Pires, G.Rita, P.Cortez, P.info:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-11-09T17:38:20Zoai:repositorio.iscte-iul.pt:10071/17467Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T22:17:32.938254Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse |
dc.title.none.fl_str_mv |
A text mining and topic modelling perspective of ethnic marketing research |
title |
A text mining and topic modelling perspective of ethnic marketing research |
spellingShingle |
A text mining and topic modelling perspective of ethnic marketing research Moro, S. Ethnic marketing Filtering dictionaries Literature analysis and synthesis Literature dimensions Text mining Topic modelling |
title_short |
A text mining and topic modelling perspective of ethnic marketing research |
title_full |
A text mining and topic modelling perspective of ethnic marketing research |
title_fullStr |
A text mining and topic modelling perspective of ethnic marketing research |
title_full_unstemmed |
A text mining and topic modelling perspective of ethnic marketing research |
title_sort |
A text mining and topic modelling perspective of ethnic marketing research |
author |
Moro, S. |
author_facet |
Moro, S. Pires, G. Rita, P. Cortez, P. |
author_role |
author |
author2 |
Pires, G. Rita, P. Cortez, P. |
author2_role |
author author author |
dc.contributor.author.fl_str_mv |
Moro, S. Pires, G. Rita, P. Cortez, P. |
dc.subject.por.fl_str_mv |
Ethnic marketing Filtering dictionaries Literature analysis and synthesis Literature dimensions Text mining Topic modelling |
topic |
Ethnic marketing Filtering dictionaries Literature analysis and synthesis Literature dimensions Text mining Topic modelling |
description |
This study presents an enhanced automated approach based on literature analysis and synthesis for establishing the dimensions of the ethnic marketing literature, covering a set of 239 journal articles published by nine major publishers. The approach reported is enhanced by two novel procedures to address previously identified limitations, namely: definition of a relevant dictionary based on both a sufficient lexicon extracted from a definition of the core theme and a conditional dictionary, with related but non-core terms; and a visually appealing pictorial representation to summarize the discovered topics. The application of the method to ethnic marketing indicates that ethnic marketing research is characterized by high conceptual heterogeneity, although a clear definition of “ethnic marketing” is imperative for research development. Overall, the paper advances an approach with considerable scalability advantages when compared with extant approaches, an important issue to consider when textual sources become big data. |
publishDate |
2019 |
dc.date.none.fl_str_mv |
2019-02-28T17:00:26Z 2019-01-01T00:00:00Z 2019 2019-02-28T16:59:45+0000 2020-02-07T00:00:00Z |
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/10071/17467 |
url |
http://hdl.handle.net/10071/17467 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
0148-2963 10.1016/j.jbusres.2019.01.053 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
Elsevier |
publisher.none.fl_str_mv |
Elsevier |
dc.source.none.fl_str_mv |
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instname_str |
Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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RCAAP |
institution |
RCAAP |
reponame_str |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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