Sentiment-Driven Modelling in Business, Economics, and Social Sciences

Dear Colleagues,

The rapid increase in digital information has brought sentiment analysis to the forefront of advanced modelling and computation in the social sciences. News articles, corporate disclosures, policy reports, online forums, and social media platforms now provide rich sources of unstructured data that reflect collective perceptions, emotions, and expectations. Sentiment, unlike traditional quantitative indicators, captures the qualitative aspect of human behaviour that often influences decision-making in markets, organizations, and societies. Integrating such measures into statistical and computational frameworks could potentially significantly enhance predictive accuracy, risk assessment, and our understanding of complex economic and social phenomena.

This Special Issue will bring together contributions that advance the theory, methodology, and applications of sentiment-driven modelling and computation. It particularly encourages research that combines sentiment extraction with statistical methods, econometric analysis, and modern machine learning techniques to generate new insights into business, finance, economics, and other fields. It will also showcase both methodological innovation and practical relevance, providing a platform for interdisciplinary dialogue at the intersection of data science and the social sciences.

Potential topics of interest include, but are not limited to, the following:

• Statistical and econometric models integrating sentiment measures;
• Machine learning and natural language processing techniques for sentiment quantification;
• Forecasting of financial markets, macroeconomic variables, and volatility using sentiment indicators;
• Behavioural models of consumer, investor, or voter sentiment;
• Sentiment analysis applied to marketing, supply chain management, and organizational performance;
• Applications in political economy, policy evaluation, and social behaviour;
• Advances in measuring uncertainty, interpretability, and robustness of sentiment-driven models;
• Interdisciplinary approaches connecting linguistics, computational methods, and applied economics.

Prof. Dr. Roman Makarov
Guest Editor

Manuscript Submission Information

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