RESEARCH TRENDS ON BIG DATA IN MARKETING: A TEXT MINING AND TOPIC MODELING BASED LITERATURE ANALYSIS

Alexandra Amado, Paulo Cortez (), Paulo Rita () and Sérgio Moro ()
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Alexandra Amado: Instituto Universitário de Lisboa (Portugal)
Paulo Cortez: University of Minho (Portugal)
Paulo Rita: Instituto Universitário de Lisboa (Portugal)

European Research on Management and Business Economics (ERMBE), 2018, vol. 24, issue 1, 1-7

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. / 0

Keywords: Big data; Marketing; Literature analysis; Research trends; Text mining (search for similar items in EconPapers)
JEL-codes: M15 M31 (search for similar items in EconPapers)
Date: 2018
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Citations: View citations in EconPapers (31)

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