Text analytics approach to examining corporate social responsibility

• Main Authors: AZHAR, Nurul Asyikeen Binte, PAN, Gary, SEOW, Poh Sun, KOH, Andrew, TAY, Wan Ying
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2019
• Subjects: Corporate social responsibility; news; content analysis; collaborative network; Singapore Exchange; MITB student; Accounting; Asian Studies; Business Law, Public Responsibility, and Ethics
• Online Access: https://ink.library.smu.edu.sg/sis_research/4375; https://ink.library.smu.edu.sg/context/sis_research/article/5378/viewcontent/Text_Analytics_Approach_CSR_2019_afv.pdf
• Institution: Singapore Management University

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