Text Analytics Approach to Examining Corporate Social Responsibility

Authors

  • Nurul Asyikeen Binte Azhar Singapore Management University
  • Gary Pan Singapore Management University School of Accountancy 60 Stamford Road Singapore 178900
  • Seow Poh Sun Singapore Management University School of Accountancy 60 Stamford Road Singapore 178900
  • Andrew Koh Singapore Management University School of Information Systems 80 Stamford Road Singapore 178902
  • Wan Ying Tay Singapore Management University School of Information Systems 80 Stamford Road Singapore 178902

Keywords:

Corporate social responsibility, GDELT, news, content analysis, collaborative network, Singapore Exchange

Abstract

This research article explores a text analytics approach to assess corporate social responsibility prominence of 554 Singapore listed firms through content analysis of news. Instead of relying on publications by the respective firms, third party news coverage is used to decrease potential biasedness through over reporting. A dataset of news articles is crawled based on the respective firm’s financial years of 2015 and 2016 and their content are parsed to search for content related to corporate social responsibility. Graph theory is then used to demonstrate the collaborative network of listed firms for corporate social responsibility activities. The results highlight a more automated and scalable means to assess prominence of corporate social responsibility as well as potential “influencers” within the corporate landscape.

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Published

2019-04-30

Issue

Vol. 11 (2019)

Section

Articles

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