A text mining and topic modelling perspective of ethnic marketing research

Sérgio Moro, Guilherme Pires, Paulo Rita, Paulo Cortez

Research output: Contribution to journalArticle

2 Citations (Scopus)

Abstract

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.

Original languageEnglish
Pages (from-to)275-285
Number of pages11
JournalJournal of Business Research
Volume103
Issue numberOctober
DOIs
Publication statusPublished - Oct 2019

Fingerprint

Text mining
Modeling
Marketing research
Marketing
Scalability

Keywords

  • Ethnic marketing
  • Filtering dictionaries
  • Literature analysis and synthesis
  • Literature dimensions
  • Text mining
  • Topic modelling

Cite this

Moro, Sérgio ; Pires, Guilherme ; Rita, Paulo ; Cortez, Paulo. / A text mining and topic modelling perspective of ethnic marketing research. In: Journal of Business Research. 2019 ; Vol. 103, No. October. pp. 275-285.
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A text mining and topic modelling perspective of ethnic marketing research. / Moro, Sérgio; Pires, Guilherme; Rita, Paulo; Cortez, Paulo.

In: Journal of Business Research, Vol. 103, No. October, 10.2019, p. 275-285.

Research output: Contribution to journalArticle

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AU - Moro, Sérgio

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AU - Rita, Paulo

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