Abstract
Investors are increasingly relying on social media to seek insights into corporate prospects. However, it remains unclear whether social executives - those engaging with stakeholders through social media - provide valuable information that shapes investors’ investment decisions, thereby influencing firm value. Drawing on emotions as social information theory, this study explores the impact of social executives’ emotions, derived from social media posts, on firm value. Moreover, we consider variances in effects across different post types and firm sizes. Applying advanced cognitive analytics and deep learning techniques, our analysis reveals a significant association between the emotions of fear and anger expressed in posts related to firm events or routine work and firm value, with more pronounced effects observed in small firms. Additionally, our machine learning experiments demonstrate that social executives’ emotions contribute to more accurate predictions of firm value than sentiments alone. These findings have important implications for both theory and practice.
Original language | English |
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Article number | 114575 |
Journal | Journal of Business Research |
Volume | 175 |
Early online date | 19 Feb 2024 |
DOIs | |
Publication status | Published - Mar 2024 |
Bibliographical note
Publisher Copyright:© 2024 Elsevier Inc.
Funding
Wang’s work was supported by grants from the National Natural Science Foundation of China (Project: 72201100), Shanghai Pujiang Program (Project: 22PJC036), and Shanghai Soft Science Project (Project: 23692121300). Lau’s work was funded by a grant from the Research Grants Council of the Hong Kong Special Administrative Region, China (Project: CityU 11507323), and a grant from the City University of Hong Kong SRG (Project: 7005780).
Keywords
- Social Executives
- Emotions
- Firm Value
- Cognitive Analytics
- Deep Learning