When Big Data Made the Headlines: Mining the Text of Big Data Coverage in the News Media

International Journal of Services Technology and Management, Forthcoming

43 Pages Posted: 26 Jul 2019

See all articles by Murtaza Haider

Murtaza Haider

Ryerson University

Amir Gandomi

Hofstra University - Frank G. Zarb School of Business

Date Written: July 24, 2019

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

Suggested Citation

Haider, Murtaza and Gandomi, Amir, When Big Data Made the Headlines: Mining the Text of Big Data Coverage in the News Media (July 24, 2019). International Journal of Services Technology and Management, Forthcoming, Available at SSRN: https://ssrn.com/abstract=3426256

Murtaza Haider

Ryerson University ( email )

Ryerson University
350 Victoria Street
Toronto, Ontario M5B 2K3
Canada
416-979-5000, x2480 (Phone)

Amir Gandomi (Contact Author)

Hofstra University - Frank G. Zarb School of Business ( email )

Hempstead, NY 11549
United States

Do you have a job opening that you would like to promote on SSRN?

Paper statistics

Downloads
103
Abstract Views
434
rank
332,366
PlumX Metrics