Research on corporate social responsibility: a big data analytics using scrapy web crawler mining technique

Jiaying Zhong

doi:10.1117/12.2672275

28 March 2023 Research on corporate social responsibility: a big data analytics using scrapy web crawler mining technique

Jiaying Zhong

Author Affiliations +

Proceedings Volume 12597, Second International Conference on Statistics, Applied Mathematics, and Computing Science (CSAMCS 2022); 125973F (2023) https://doi.org/10.1117/12.2672275
Event: Second International Conference on Statistics, Applied Mathematics, and Computing Science (CSAMCS 2022), 2022, Nanjing, China

Abstract

In this paper, we made a significant effort to identify actual online data to justify why analyst coverage is essential in corporate social responsibility practice. A total of 5856 datasets were drawn from three listed company information websites using the Scrapy web crawlers to investigate a resilience model in the relationship between analyst coverage, executive overseas background and corporate social responsibility. Based on big data analysis, we observe that firms followed by more analysts perform better in corporate social responsibility. The relationship is stronger for firms that have executives with overseas background. Our findings shed light on how firms choose their corporate social responsibility performance under external supervision pressure of analysts.

Citation Download Citation

Jiaying Zhong "Research on corporate social responsibility: a big data analytics using scrapy web crawler mining technique", Proc. SPIE 12597, Second International Conference on Statistics, Applied Mathematics, and Computing Science (CSAMCS 2022), 125973F (28 March 2023); https://doi.org/10.1117/12.2672275

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