International Conference on Data Analytics, Information Science, and AI (ICDAISA - 26)

This track explores the integration of data analytics in social science research, emphasizing methodologies that enhance decision-making processes. Participants will discuss case studies and frameworks that leverage data to inform policy and practice in various social contexts.

This session focuses on the application of artificial intelligence techniques in the humanities, examining how AI can facilitate new insights and interpretations. Scholars will present innovative projects that utilize AI to analyze historical texts, art, and cultural artifacts.

This track highlights the use of machine learning algorithms in social research, showcasing their potential to uncover patterns and trends in complex datasets. Presentations will cover diverse applications, from survey analysis to social media data mining.

This session investigates the implications of big data on societal structures and individual behaviors, addressing both opportunities and challenges. Researchers will present findings on how big data analytics can shape public opinion, consumer behavior, and social interactions.

This track delves into the methodologies of knowledge discovery within social networks, focusing on techniques that extract meaningful insights from social media and online interactions. Participants will share research on network analysis, sentiment analysis, and community detection.

This session examines the role of predictive analytics in shaping social policy and governance, highlighting tools that forecast social trends and outcomes. Researchers will discuss ethical considerations and the effectiveness of predictive models in real-world applications.

This track focuses on computational techniques and their applications in information science, emphasizing algorithm development and data processing. Presenters will explore advancements in computational methods that enhance data retrieval, storage, and analysis.

This session addresses the ethical implications of using AI and data analytics in social research, focusing on issues of privacy, consent, and bias. Scholars will engage in discussions about best practices and frameworks for ethical research in the digital age.

This track promotes interdisciplinary collaboration in data science, encouraging participants to share insights from various fields such as sociology, psychology, and cultural studies. Presentations will highlight how diverse perspectives can enrich data analysis and interpretation.

This session explores the development and implementation of information systems designed to promote social change and community engagement. Researchers will present case studies demonstrating the impact of these systems on social initiatives and public awareness.

This track focuses on the latest trends in data visualization techniques tailored for social science research, emphasizing clarity and accessibility. Participants will discuss innovative visual tools that enhance the communication of complex data to diverse audiences.