Can Negative Emotions on Social Media Predict Corporate Financial Risks: Perspective from Baidu Tieba

Authors

  • Jingyang Ma

DOI:

https://doi.org/10.61173/bf27vs81

Keywords:

Social Media, Negative Sentiment, Financial Risk, Baidu Post Bar

Abstract

The intrinsic relationship between social media and corporate development has emerged as one of the key research topics today. Most current studies focus on the positive impacts and opportunities that social media can bring to enterprises. However, there remains a lack of a unified explanation for the influence of negative news on social media on businesses. Consequently, the research theme of this paper is to explore whether negative sentiments on social media can predict corporate financial risks. Firstly, this paper collects data related to bearish posts on social media and financial risks of enterprises. Subsequently, regression analysis is conducted on the data using SPSS. The results reveal that, under the condition of controlling the asset-liability ratio, negative posts on social media do have an impact on corporate financial risks, with a greater number of negative posts correlating to a higher level of financial risk for the enterprise. This paper fills a gap in understanding the negative implications of social media on certain aspects of businesses and provides data support for researching the influence of negative sentiments on social media on corporate financial risks.

References

[1] Liu, Y., Liu, M., Wang, G. et al. Effect of Environmental Regulation on High-quality Economic Development in China— An Empirical Analysis Based on Dynamic Spatial Durbin Model. Environmental Science And Pollution Research, 2021, 28: 54661–54678.

[2] Zhou Fei. Research on the Impact of Corporate Social Responsibility Negative Information Disclosure Strategies on Investors’ Investment Decisions. Jiangxi: East China Jiaotong University, 2023.

[3] Thomson Reuters Global Resources Inc. Method and system for generating a corporate green score using data and sentiment analysis derived from social media: CN201280070735.0. 2014.

[4] Zhao Huanli. Is Corporate Social Media a Double-Edged Sword? - A Study on Technological Stress Among Frontline Hotel Employees,Sichuan: Southwestern University of Finance and Economics, 2023.

[5] Zulaikah, S., and N. Laila. Perbandingan Financial Distress Bank Syariah Di Indonesia Dan Bank Islam Di Malaysia Sebelum Dan Sesudah Krisis Global 2008 Menggunakan Model Altman ZScore. Jurnal Ekonomi Syariah Teori Dan Terapan,2016, 3(11): 900-914

[6] Santoni, V. La Previsione dell’insolvenza aziendale: confronto della performance dei modelli Zscore, Logit e Random Forest su un campione di aziende manifatturiere italiane, 2014.

[7] Angga, L.I.Analisis pengaruh kebangkrutan perusahaan manufaktur dengan metode altman zscore terhadap harga saham perusahaan manufaktur di bursa efek indonesia tahun 2007- 2009, 2012.

[8] Yee Loon Mun1, Hassanudin Mohd Thas Thaker2,Asset Liability Management of Conventional and Islamic Banks in Malaysia. Journal of Islamic Economics, 2017, 9 (1).

[9] Setayesh, M. H., & Fatheh, M. H.. Examining the Effects of Healthy Banking Indicators in Determining the Asset-Liability Management (ALM) Strategy by Focusing on Capital Adequacy Ratio (CAR) Index Journal of Investment Knowledge, 2017, 6(24): 139-150.

[10] Shen, J. and Yin, X.Credit expansion, state ownership and capital structure of Chinese real estate companies, Journal of Property Investment & Finance,2016, 34(3): 263-275.

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Published

2024-10-29