Text analytics approach to examining corporate social responsibility

• Main Authors: Nurul Asyikeen Azhar,, Pan, Gary, Seow, Poh Sun, Koh, Andrew, Tay, Wan Ying
• Format: Article
• Language: English
• Published: Penerbit Universiti Kebangsaan Malaysia 2019
• Online Access: http://journalarticle.ukm.my/15298/1/25077-100815-2-PB.pdf; http://journalarticle.ukm.my/15298/; http://ejournal.ukm.my/ajac/issue/view/1184

This research article explores a text analytics approach to assess the prominence of corporate social responsibility in 554 Singapore-listed firms through a content analysis of the news. Instead of relying on publications by the firms, third-party news coverage is used to reduce potential biases due to over-reporting. A dataset of news articles on the included firms published during fiscal years 2015 and 2016 is crawled, and the articles’ content is parsed to search for information related to corporate social responsibility. Graph theory is subsequently used to create a collaborative network of listed firms’ corporate social responsibility activities. The results highlight a more automated and scalable means of assessing the prominence of corporate social responsibility, as well as potential “influencers” within the corporate landscape.