A text mining and topic modelling perspective of ethnic marketing research

Detalhes bibliográficos
Autor(a) principal: Moro, S.
Data de Publicação: 2019
Outros Autores: Pires, G., Rita, P., Cortez, P.
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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spelling 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
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status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/10071/17467
url http://hdl.handle.net/10071/17467
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language eng
dc.relation.none.fl_str_mv 0148-2963
10.1016/j.jbusres.2019.01.053
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publisher.none.fl_str_mv Elsevier
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