Research trends on Big Data in Marketing: A text mining and topic modeling based literature analysis

Alexandra Amado, Paulo Cortez, Paulo Rita, Sérgio Moro

Research output: Contribution to journalArticlepeer-review

80 Citations (Scopus)
374 Downloads (Pure)

Abstract

Given the research interest on Big Data in Marketing, we present a research literature analysis based on a text mining semi-automated approach with the goal of identifying the main trends in this domain. In particular, the analysis focuses on relevant terms and topics related with five dimensions: Big Data, Marketing, Geographic location of authors' affiliation (countries and continents), Products, and Sectors. A total of 1560 articles published from 2010 to 2015 were scrutinized. The findings revealed that research is bipartite between technological and research domains, with Big Data publications not clearly aligning cutting edge techniques toward Marketing benefits. Also, few inter-continental co-authored publications were found. Moreover, findings show that research in Big Data applications to Marketing is still in an embryonic stage, thus making it essential to develop more direct efforts toward business for Big Data to thrive in the Marketing arena.

Original languageEnglish
Pages (from-to)1-7
Number of pages7
JournalEuropean Research on Management and Business Economics
Volume24
Issue number1
Early online date2017
DOIs
Publication statusPublished - 2018

Keywords

  • Big data
  • Literature analysis
  • Marketing
  • Research trends
  • Text mining

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