Research trends on Big Data in Marketing: A text mining and topic modeling based literature analysis
By Alexandra Amado, Paulo Cortez, Paulo Rita, Sérgio Moro. European Research on Management and Business Economics, 2018
302 citations recorded by the source corpus.
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.
Subfields: Management Information Systems, Marketing, Sociology and Political Science
View Paper: https://www.semanticscholar.org/paper/36dbfc2ed2c8cf156a0df6957643f21af5aef92b
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Sociology and Political Science
Citations in the corpus
- Text Mining in Big Data Analytics (2020, methodology): “[203], based on the study of Moro et al.”