The program aims to cultivate the skills necessary for converging and utilizing knowledge of the humanities and social sciences with digital/computing/artificial intelligence technologies through common methodologies and intensive methodology courses for each major track as well as intensive courses on research topics in the major track, alongside project and seminar courses.

• - Major required

  Major required

  Course	Overview
  Introduction to Digital Humanities and Computational Social Sciences	Understand how various topics in the humanities and social sciences are researched using digital information and data analysis technology, learning about the characteristics and trends in the digital humanities and social sciences
  Programming for Humanities and Social Science Research	Obtain programming and computational thinking skills required for conducting digital humanities and social sciences research. Practice using R and Python to solve various problems in the humanities and social sciences

• - Major elective I: Designated elective (Methodology)

  Major elective I: Designated elective (Methodology)

  Course	Overview
  Humanities, Social Sciences and Database Theory	Metadata processing, database building and management for digital humanities and social sciences
  Humanities, Social Sciences and Natural Language Processing	Theory and practice of natural language processing methods (Bert, GPT etc.) related to digital humanities and social sciences
  Humanities, Social Sciences and Machine Learning	Theory and practice of machine learning related methodologies (regression analysis, kernel function, deep learning etc.) for digital humanities and social sciences
  Data Science for Humanities and Social Sciences	Learn methods for collecting and organizing big data for the humanities and social sciences, and skills for effective data clustering and visualization
  Statistical Theory and Practice for Humanities and Social Science Research	Learn various statistical methodologies for analyzing humanities and social science data and practice using statistical programs in data analysis
  Network Analysis Theory and Practice	Understand and practice network analysis in social science through the exploration of relationships and centrality in networks
  Experimental Research Methodology for Humanities and Social Sciences	Experiment techniques, design, data analysis to understand experimental methodologies in the humanities and social sciences (e.g. behavioral observation, online experiments, experiments to measure physiological response)

• - Major elective II: Intensive elective
  • Digital humanities

    Digital humanities

    Course	Overview
    Special Topics in Digital Humanities	Intensively learn and analyse in digital humanities for various types of content such as literature, history, and classics and propose digital humanities research topics
    Data-based Narratology	Learn theory for understanding narratives in the digital age and practice narrative analysis and evaluation based on data
    Humanity in the AI Era	Humanities-based analysis and reflection on humans and humanity in the AI era. Vision for humanity and civilization in the post-AI era and proposals for sustainable development
    Quantitative Analysis of Text	Advanced quantitative analysis of text in the field of humanities. In particular, practice quantitative text analysis on literary text character structures, emotions, topic modelling, etc.
    Spatial Reproduction and Digital Study of History	Focusing on the visual reproduction of historical changes to a space based on primary sources, exploring methodologies in digital history studies, and practice in online themed archive building

  • Computational Social Science

    Computational Social Science

    Course	Overview
    Special Topics in Computational Social Science	Discuss various social science issues and propose, design, and execute projects based on these discussions
    Big Data, AI & Society	Learn key technologies related to big data and human society, discussing the associated moral, ethical and legal issues
    Human-Computer Communication	Explore the active co-existence and communication between human and computers and discuss potential applications
    Computational Social Science Research Using Environmental Energy Data	Learn applied theories in big data analysis and practice using big data from real world environmental energy
    ‘Social Issue’ Studies: Theory and Methods	Explore traditional research questions and issues in social science through theories and methodologies
    Contemporary Computational Social Sciences	Read the latest papers on computational social sciences, exploring research topics and methodologies
    Computing Analysis of Social Processes	Understand trends in computing analysis of social processes such as social interactions and formation of culture, as well as key limitations

  • Linguistics & Psychological Science

    Linguistics & Psychological Science

    Course	Overview
    Special Topics in Linguistics & Psychological Science	Learn advanced research topics and methodologies in linguistics and psychological science. Project proposal and execution included.
    Cognitive Science and its Applications	Understand the characteristics of cognitive processes (perception, attention, memory, selection, decision-making etc.) through multi-disciplinary approaches, exploring possibilities in actualizing creative artifacts
    Music and Cognitive Science	Learn the cognitive processing of musical elements such as rhythm and pitch, with an introduction to related research
    Language and Cognition	Explore the linguistic and cognitive processes occurring in the language production and comprehension in various communicative situations, and learn related research
    Art Analysis through Brain Information Processing	Grounded on common properties in neuroscience, psychology, cognitive science, and neuroesthetics, explore the complex relationship between science and art from a transdisciplinary perspective
    Data Science and Linguistic Culture	Analyze language based on big data and AI to investigate the relationship between language and culture. Understand various sociocultural elements in language using sociolinguistic perspective
    AI and Human Learning	Learn theories on human learning and language acquisition processes. Attempt a psychological approach to language learning. Explore applications such as language education using AI and computers
    Visual Cognition Computational Models	Explore computational models that can reflect the processes associated with vision and cognition