Cheap Talk: Topic Analysis of CSR Themes on Corporate Twitter

Nile Phillips, Sathvika Anand, Michelle Lum, Manisha Goel, Michelle Zemel, Alexandra Schofield


Abstract
Numerous firms advertise action around corporate social responsibility (CSR) on social media. Using a Twitter corpus from S&P 500 companies and topic modeling, we investigate how companies talk about their social and sustainability efforts and whether CSR-related speech predicts Environmental, Social, and Governance (ESG) risk scores. As part of our work in progress, we present early findings suggesting a possible distinction in language between authentic discussion of positive practices and corporate posturing.
Anthology ID:
2024.finnlp-1.20
Volume:
Proceedings of the Joint Workshop of the 7th Financial Technology and Natural Language Processing, the 5th Knowledge Discovery from Unstructured Data in Financial Services, and the 4th Workshop on Economics and Natural Language Processing
Month:
May
Year:
2024
Address:
Torino, Italia
Editors:
Chung-Chi Chen, Xiaomo Liu, Udo Hahn, Armineh Nourbakhsh, Zhiqiang Ma, Charese Smiley, Veronique Hoste, Sanjiv Ranjan Das, Manling Li, Mohammad Ghassemi, Hen-Hsen Huang, Hiroya Takamura, Hsin-Hsi Chen
Venue:
FinNLP
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
203–211
Language:
URL:
https://aclanthology.org/2024.finnlp-1.20
DOI:
Bibkey:
Cite (ACL):
Nile Phillips, Sathvika Anand, Michelle Lum, Manisha Goel, Michelle Zemel, and Alexandra Schofield. 2024. Cheap Talk: Topic Analysis of CSR Themes on Corporate Twitter. In Proceedings of the Joint Workshop of the 7th Financial Technology and Natural Language Processing, the 5th Knowledge Discovery from Unstructured Data in Financial Services, and the 4th Workshop on Economics and Natural Language Processing, pages 203–211, Torino, Italia. Association for Computational Linguistics.
Cite (Informal):
Cheap Talk: Topic Analysis of CSR Themes on Corporate Twitter (Phillips et al., FinNLP 2024)
Copy Citation:
PDF:
https://aclanthology.org/2024.finnlp-1.20.pdf