Date: 14th & 15th February 2026 | Time: 9.00 am – 1:00 pm (IST) | Location: Online

Overview:

This conference focuses on leveraging big data, including market sentiment and unstructured data sources such as social media, news, and alternative datasets, for enhanced economic forecasting. It emphasizes integrating traditional econometric models with machine learning and natural language processing to improve accuracy and timeliness of economic predictions. The event highlights challenges and innovations in data processing, sentiment analysis, and real-time analytics for macroeconomic monitoring and decision-making.

Structure and Sessions (Who Does What):

• Organizing Committee: Plans agenda, selects keynote speakers and experts, and manages online event coordination.
• Keynote Speakers: Economists, data scientists, and sentiment analysis experts deliver foundational insights and forward-looking perspectives.
• Session Chairs: Moderate sessions, facilitate Q&A, and ensure participant engagement.
• Presenters: Researchers and practitioners share case studies, methodologies, and empirical findings.
• Participants: Engage actively in workshops, discussions, and networking.
• Technical Review Committee: Reviews paper submissions for quality and relevance.

Participate and Contribute (Who Benefits):

• Economic Forecasters and Data Scientists: Learn methods to incorporate diverse data sources for better economic predictions.
• Policy Makers and Central Bankers: Understand how big data enables real-time monitoring of economic conditions.
• Academics and Researchers: Present research and contribute to scholarly discourse.
• Financial Analysts and Strategists: Gain insights into market sentiment impacts on economic outcomes.
• Technology Developers: Explore tools and platforms supporting big data economic forecasting.

Benefits:

• Certificate of Participation awarded upon submitting event feedback.
• Commemorative momento recognizing participation and contribution.
• Abstracts and selected papers published in top indexed journals including Scopus, CrossRef, Web of Science (WoS), Elsevier, and Science Citation Index (SCI).

Abstract Topics / Call for Papers (CFP) Tracks:

• Big Data Integration in Macroeconomic Forecasting
• Sentiment Analysis and Natural Language Processing for Economics
• Machine Learning Applications for Nowcasting and Forecasting
• Alternative Data Sources and Their Economic Implications
• Real-Time Economic Data Processing and Visualization
• Case Studies on Big Data-Empowered Economic Forecasts
• Network and Text Mining Techniques in Economic Analysis
• Challenges in Data Quality and Governance
• Policy Impact Assessment Using Big Data
• Future Trends in Economic Forecasting Technologies

Registration:

• Online registration open to economists, data scientists, policy makers, researchers, and students.
• Clear submission guidelines and deadlines for abstracts and papers.
• Access to live sessions, recorded materials, conference certification, and publication pathways.

Detailed Program Grid (2 Half Days, 9 AM to 1 PM)

This conference offers cutting-edge research and practical applications on economic forecasting with big data, supported by certification and publication options.