Political sentiment and syndicated loan borrowing costs of multinational enterprises

Karavitis, Panagiotis; Kazakis, Pantelis

doi:10.1016/j.intfin.2022.101537

Cited by 5 publications

(1 citation statement)

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“…The banking industry is not the only sector that has harnessed the potential of sentiment analysis to its advantage, as several political interest groups produced policy imperatives in the face of the recurrent use of this type of analysis. For example, Karavitis and Kazakis (2022) studied the borrowing costs of U.S. firms with foreign subsidiaries whose political exposure was evident and concluded that an increase in the positive political sentiment of the firm produces a drop in borrowing costs. In addition, the negative effect of a high lending cost in countries with foreign subsidiaries where political polarization is higher is mitigated.…”

Section: Opinion Mining In the Banking Sectormentioning

confidence: 99%

Computational Linguistic and SNA to Classify and Prevent Systemic Risk in the Colombian Banking Industry

Moreno-Sandoval

Rojas

Pomares-Quimbaya

et al. 2023

International Journal of E-Business Research

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The banking sector has been one of the first to identify the importance of social media analysis to understand customers' needs to offer new services, segment the market, build customer loyalty, or understand their requests. Users of Social Networking Sites (SNS) have interactions that can be analyzed to understand the relationships between people and organizations in terms of structural positions and sentiment analysis according to their expectations, opinions, evaluations, or judgments, what can be called collective subjectivity. To understand this dynamic, this study performs a social network analysis combined with computational linguistics through opinion mining to detect communities, understand structural relationships, and manage a Colombian case study's reputation and systemic risk in the banking industry. Finagro and BancoAgrario are the network leaders in both centralities, most of the main actors have a negative polarity, and MinHacienda and cutcolombia with totally different orientations appear in all methods.

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Section: Opinion Mining In the Banking Sectormentioning

confidence: 99%