Title: When big data made the headlines: mining the text of big data coverage in the news media

Authors: Murtaza Haider; Amir Gandomi

Addresses: Ted Rogers School of Management, Ryerson University, 350 Victoria Street, Toronto ON M5B 2K3, Canada ' Frank G. Zarb School of Business, Hofstra University, 1000 Hempstead Turnpike, Hempstead, NY 11549, USA

Abstract: Big data-driven analytics emerged as one of the most sought-after business strategies of the decade. This paper reviews the news coverage of this phenomenon in the popular press. The study uses natural language processing (NLP) and text mining algorithms to determine the focus and tenor of the news media reporting of big data. A detailed content analysis of a five million-word corpus reveals that most news coverage focused on the newness of big data technologies that showcased usual suspects in big data geographies and industries. The insights gained from the text analysis show that big data news coverage indeed evolved where the initial focus on the promise of big data moderated over time. This study also offers a detailed exposé of text mining and NLP algorithms and illustrates their application in news content analysis.

Keywords: big data; news content analysis; text mining; natural language processing; NLP; topic modelling; modal verb analysis.

DOI: 10.1504/IJSTM.2021.113574

International Journal of Services Technology and Management, 2021 Vol.27 No.1/2, pp.23 - 50

Accepted: 11 Apr 2019
Published online: 12 Mar 2021 *

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