Text Analytics Approach to Examining Corporate Social Responsibility

Nurul Asyikeen Binte Azhar, Gary Pan, Seow Poh Sun, Andrew Koh, Wan Ying Tay

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.

Keywords


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

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