The research method is the cornerstone of academic literacy, and the rise of Artificial Intelligence (AI) is reshaping both the practical pathways and cognitive approaches of research methodology. AI not only enhances research efficiency but also profoundly influences researchers’ problem awareness, analytical styles, and modes of knowledge production. As philosopher of science Norwood Russell Hanson notes in Patterns of Discovery: “What the observer sees is shaped by the paradigm through which they look; they notice what others overlook in the seemingly familiar.”
In our view, research methods in the social sciences are fundamentally “paradigms for observing the world.” Today, these paradigms are being redefined by AI tools. In response, the Poros team is launching a new workshop: “How to Use AI Tools in Social Science Research.”
This workshop is designed for social science researchers seeking to enhance research efficiency and innovation. It systematically demonstrates how to integrate AI tools into every stage of research—problem formulation, literature review, research design, data collection and analysis, and academic writing—empowering the entire research process.
Course Objectives
- Master general techniques for using mainstream AI tools
- Learn how to use AI for problem construction and research design
- Improve literature search and review efficiency with AI
- Understand AI’s capabilities in data collection and data analysis
- Learn how AI can assist in drafting academic manuscripts
- Be able to independently integrate AI tools to complete a theoretically rigorous social science study
Ideal Participants
- University faculty with some research background who wish to learn AI-assisted research skills
- Researchers preparing theses or journal articles who want to improve efficiency and quality using AI
- Learners wishing to understand the practical functions of AI in quantitative/qualitative research and academic writing
Course Schedule
Start Date: November 5, 2025
End Date: December 24, 2025
Duration: 8 weeks, 20 class hours
Instructors
- Professor and PhD Supervisor, School of Journalism and Communication, Tsinghua University
- Professor and PhD Supervisor, School of Artificial Intelligence, Shanghai Jiao Tong University
Teaching Format
The course consists of live online lectures + after-class Q&A.
- Live online lectures: Once per week, 2 hours each, with real-time interaction. All sessions are recorded for replay at any time.
- After-class Q&A: A class group will be created; instructors and teaching assistants will be available to answer questions and provide guidance throughout the course.
Course Fees
- 4,800 RMB per person
- 10% off for group enrollment of two or more
- Free trial available for the first two sessions before payment
- Refunds available within two weeks after the course begins
- Invoices can be issued upon payment
Course Features
- AI-focused: Hands-on training with cutting-edge tools to boost research efficiency
- Practice-oriented: Each session includes cases, demonstrations, and exercises
- Support for research output: Participants may submit personal projects for optional one-on-one instructor feedback
- Expert teaching team: Faculty experienced in both AI tools and social science research, with extensive expertise in AI-assisted academic writing and publication
Course Content
Week 1: Course Introduction
- Overview of AI development: from early AI to modern deep learning and NLP
- How AI is revolutionizing research paradigms in the social sciences
- A landscape of AI tools in research: design, literature review, data analysis, writing
- Ethical challenges in AI-assisted research: privacy, bias, credibility
- Best practices: balancing AI with originality and academic rigor
Week 2: Problem Formulation & Research Design
- Using AI to identify research frontiers and gaps (e.g., Elicit, Scite)
- AI-assisted problem refinement and hypothesis generation
- Constructing research frameworks: mapping variables, logic, and methodology
- Exercise: Use AI to draft a structured research proposal outline
Week 3: Literature Management & Analysis
- AI-enhanced reference tools: Zotero + scite.ai, Endnote with AI plugins
- Literature understanding and synthesis: keyword extraction, summarization, topic clustering (GPT, HuggingFace)
- Generative AI for literature review drafting: from search to initial writing
- Case practice: Use GPT + Elicit to generate and refine a short review paragraph
Week 4: Data Collection & AI-Assisted Preprocessing
- Data acquisition methods: web scraping, survey tools with AI plugins
- AI and machine learning for data cleaning and missing-value imputation
- AI-assisted data augmentation: corpus expansion
- Case practice: Collect and preprocess social media data
Week 5: Statistical Analysis & Visualization
- AI in statistical modeling (regression, clustering, logistic regression)
- ChatGPT + Python + Streamlit for automated analysis
- Basics of visualization with Matplotlib
- Interactive visualization using Tableau & Power BI
- Case study: Generate a social science research report with analysis & visualization
Week 6: NLP & Qualitative Research
- NLP fundamentals and tools (spaCy, NLTK, GPT)
- Automated coding, text classification, sentiment analysis
- Topic modeling (LDA) and key theme extraction
- Case practice: Analyze interview and social media text to identify emotions and topics
Week 7: Academic Writing & International Publishing Strategies
- AI-assisted academic writing and language polishing
- Using AI to identify target journals and prepare submission materials
- Demonstration: Optimize the language and structure of a social science paper using AI tools
Week 8: Course Summary
- Review of all course content to ensure mastery of AI-assisted research
- Outlook: the future of AI in social science research
- Guidance for designing individualized AI-assisted research workflows
Registration Information
Registration Period: August 25 – November 1, 2025
Email: info@poroschronicle.com
WeChat: poros2022
How to Register: Scan the QR code below and complete the registration form.
