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

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Computation is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1800 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

• sentiment analysis
• natural language processing (NLP)
• machine learning
• statistical modelling
• behavioural economics
• business and financial analytics
• computational social science