Digital Disruption: A Corpus-based Analysis of Keywords in the Bangkok Post Newspaper (January 2017-February 2018)

Abstract

The ultimate goal of this research study is to investigate the information relating to the phenomenon of digital disruption that is presented to the public by the media. Employing mixed method of analysis, 81 news articles that were reported from January 2017 to February 2018 Thailand's leading English newspaper, The Bangkok Post, composed of 101,895 words, were examined for keywords. Using the free corpus tool AntConc, the investigation was done by comparing words, with a minimum absolute frequency of 100, against their frequencies in the British National Corpus (BNC) using log-likelihood (see Rayson & Garside, 2000 for details of log-likelihood uses). Any words with a log-likelihood (LL) value greater than 100 were considered keywords. The resulting keywords were iteratively thematized by each of the researcher, and the degree of inter-rate agreement for accuracy and reliability in categorization is expressed as Cohen's kappa value. The analysis yield 34 keywords composed of words relating to digital technology and its applications (N=11; 32.35%), words relating to business and monetary issues (N=10; 39.41%), words relating to digital technology potential stakeholder (N=5; 14.71%), words relating to digital technology impact (N=3; 8.82%), words relating to location and time (N=3; 8.82%), and words relating to informational dimension of language (N=2; 5.82%), with the analysis categorization having a substantial level of inter-rater agreement (Cohen's kappa=0.785).