| Issue |
E3S Web Conf.
Volume 409, 2023
International Conference on Management Science and Engineering Management (ICMSEM 2023)
|
|
|---|---|---|
| Article Number | 03009 | |
| Number of page(s) | 11 | |
| Section | Data Science | |
| DOI | https://doi.org/10.1051/e3sconf/202340903009 | |
| Published online | 01 August 2023 | |
Combining Big Data Analysis to Study the Relationship between the Tone of CSR Reports and Information Asymmetry
1 School of Business, Sichuan University, Chengdu 610065, People’s Republic of China
2 School of Physical Education, Sichuan University, Chengdu, People’s Republic of China
* e-mail: lfyue@scu.edu.cn
Big data mining and analytics help uncover hidden patterns and correlations in business. It serves as the optimal tool to interpret the behavior of companies in specific environments. Built on the large amount of data obtained from various sources, this paper examines the relationship between the tone of corporate social responsibility(CSR) reports and the degree of information asymmetry between investors and managers. Python software is used for data collection, text analysis, and word frequency statistics. The results show that the tone of the social responsibility report reduces the degree of information asymmetry, indicating that the tone of the social responsibility report has an incremental information effect. Further analysis shows that the tone of CSR reports significantly reduces information asymmetry in companies with optimistic forecasts and high media attention.
Key words: Big data / Corporate social responsibility / Disclosure tone / Information asymmetry
© The Authors, published by EDP Sciences, 2023
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.