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A text mining and topic modelling perspective of ethnic marketing research

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  • Moro, Sérgio
  • Pires, Guilherme
  • Rita, Paulo
  • Cortez, Paulo

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.

Suggested Citation

  • Moro, Sérgio & Pires, Guilherme & Rita, Paulo & Cortez, Paulo, 2019. "A text mining and topic modelling perspective of ethnic marketing research," Journal of Business Research, Elsevier, vol. 103(C), pages 275-285.
  • Handle: RePEc:eee:jbrese:v:103:y:2019:i:c:p:275-285
    DOI: 10.1016/j.jbusres.2019.01.053
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    References listed on IDEAS

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    2. Chatzopoulou, Elena & Navazhylava, Kseniya, 2022. "Ethnic brand identity work: Responding to authenticity tensions through celebrity endorsement in brand digital self-presentation," Journal of Business Research, Elsevier, vol. 142(C), pages 974-987.
    3. Hugo S. Gonçalves & Sérgio Moro, 2023. "On the economic impacts of COVID‐19: A text mining literature analysis," Review of Development Economics, Wiley Blackwell, vol. 27(1), pages 375-394, February.
    4. Venkatesh Shankar & Sohil Parsana, 2022. "An overview and empirical comparison of natural language processing (NLP) models and an introduction to and empirical application of autoencoder models in marketing," Journal of the Academy of Marketing Science, Springer, vol. 50(6), pages 1324-1350, November.
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    8. Julio Cesar Alonso Cifuentes, 2020. "Una introducción a la construcción de Word Clouds (para economistas) en R," Icesi Economics Lecture Notes 18187, Universidad Icesi.
    9. Mohamed M. Mostafa, 2023. "A one-hundred-year structural topic modeling analysis of the knowledge structure of international management research," Quality & Quantity: International Journal of Methodology, Springer, vol. 57(4), pages 3905-3935, August.
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