The usage of large data sets in online consumer behaviour: A bibliometric and computational text-mining–driven analysis of previous research

Mika Vanhala, Chien Lu, Jaakko Peltonen, Sanna Sundqvist, Jyrki Nummenmaa, Kalervo Järvelin

Tutkimustuotos: LehtiartikkeliArticleScientificvertaisarvioitu

78 Sitaatiot (Scopus)
131 Lataukset (Pure)

Abstrakti

The paper reports the evolution of scientific research on usage of large datasets in online consumer behaviour between 2000 and 2018. Thus, it affords information regarding the evolution of the field in terms of identifying key publications and authors as well as how certain topics have evolved over time. In addition, by utilising topic modelling and text analytic techniques, it is identified certain research themes from the papers within the published articles included in the dataset. This offers a guide to those who want to contribute to the field. In addition, paper contributes to the methodology related to literature surveys and bibliometric analyses by conducted topic modelling to extract the latent topics from the collected literature by utilising Structural Topic Modelling in order to gain more elaborated results.
AlkuperäiskieliEnglanti
Sivut46-59
Sivumäärä14
JulkaisuJournal of Business Research
Vuosikerta106
Numero1
Varhainen verkossa julkaisun päivämäärä2019
DOI - pysyväislinkit
TilaJulkaistu - tammik. 2020
OKM-julkaisutyyppiA1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä

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