Промышленная инженерия и менеджмент

Applications of Text Mining in the Construction Sector

Abstract

L. Marin

Given the interest in big Data in marketing research, we present a semi-automated text mining-based research literature analysis with the aim of identifying the main trends in this field. In particular, the analysis focuses on five relevant dimensions and terms: Marketing, big data, the countries and continents of authors' affiliation, products and industries 1560 published articles from were examined in total. Big Data publications did not clearly align cutting edge marketing techniques with benefits, indicating that research is bipartite between technological and research domains. Additionally, there were only a few publications with co-authors across continents. Additionally, the findings indicate that big Data applications to marketing research are still in its infancy. As a result, for Big Data to thrive in marketing, more focused efforts toward business must be made. Unstructured data generated by new communication technologies and user editing platforms (e.g., text, images and videos) and structured data generated by organizations traditional databases are both forms of Big Data that are currently prevalent. Customer’s decisions are being significantly influenced by social media platforms like Facebook and twitter, leading businesses and brands to incorporate information from these platforms into their marketing strategies. As a result, Big Data is expanding.