Record Details

Text Analytics Approach to Examining Corporate Social Responsibility

Asian Journal of Accounting and Governance

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Field Value
 
Title Text Analytics Approach to Examining Corporate Social Responsibility
 
Creator Azhar, Nurul Asyikeen Binte
Pan, Gary
Poh Sun, Seow
Koh, Andrew
Tay, Wan Ying
 
Subject Corporate social responsibility, GDELT, news, content analysis, collaborative network, Singapore Exchange
 
Description 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.
 
Publisher Penerbit UKM
 
Contributor Singapore Management University
 
Date 2019-04-30
 
Type info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
Peer-reviewed Article
 
Format application/pdf
 
Identifier http://ejournal.ukm.my/ajac/article/view/25077
 
Source Asian Journal of Accounting and Governance; Vol 11 (2019)
2180-3838
 
Language eng
 
Relation http://ejournal.ukm.my/ajac/article/view/25077/9287
http://ejournal.ukm.my/ajac/article/downloadSuppFile/25077/11892
http://ejournal.ukm.my/ajac/article/downloadSuppFile/25077/11893
http://ejournal.ukm.my/ajac/article/downloadSuppFile/25077/11894
http://ejournal.ukm.my/ajac/article/downloadSuppFile/25077/11895
 
Rights Copyright (c) 2019 Asian Journal of Accounting and Governance