This track focuses on the application of data analytics in social science research, emphasizing how data-driven approaches can enhance decision-making processes. Participants will explore case studies and methodologies that illustrate the integration of data science in social research.

This session examines the role of artificial intelligence in transforming humanities research, including text analysis and digital archiving. Scholars will discuss innovative AI applications that facilitate new insights and interpretations in the humanities.

This track investigates the impact of big data on social change, exploring how large datasets can inform policy-making and societal trends. Researchers will present findings on the intersection of big data analytics and social issues.

This session delves into machine learning methodologies applied within information systems, highlighting their effectiveness in enhancing data management and retrieval. Participants will share research on algorithm development and system optimization.

This track focuses on the utilization of deep learning techniques in social research, showcasing their potential for analyzing complex datasets. Presenters will discuss innovative applications and the implications of deep learning in understanding social phenomena.

This session explores knowledge discovery processes within the digital humanities, emphasizing the extraction of meaningful insights from digital data sources. Researchers will present methodologies and tools that facilitate knowledge generation in this field.