Intelligent research design for data intensive social science
Who we serve D-Lab helps UC Berkeley undergraduate students, graduate students, faculty, and staff move forward with world-class research in data intensive social science and humanities.
What we do D-Lab assists the Berkeley community with the full range of research development, research design and data acquisition. We offer guidance in statistical methods and results to data visualization and communication.
Who we are D-Lab is comprised of scholars who create a learning community that teaches workshops and offers consultations. Join us!
by María Martín López. As large language models begin to engrain themselves in our daily lives we must leverage cognitive psychology to explore the understanding that these algorithms have of our world and the people they interact with. LLMs give us new insights into how conceptual representations...Read more about Conceptual Mirrors: Reflecting on LLMs' Interpretations of Ideas
by Hilary Faxon, Ph.D. & Win Moe. Non-Roman scripts pose particular challenges for text mining. Here, we reflect on a project that used text mining alongside qualitative coding to understand the politicization of online content following Myanmar’s 2021 military coup.Read more about Tactics for Text Mining non-Roman Scripts
by Kamya Yadav. With the increase in studies with experiments in political science research, there are concerns about research transparency, particularly around reporting results from studies that contradict or do not find evidence for proposed theories (commonly called “null results”). To...Read more about Transparency in Experimental Political Science Research
by Alex Ramiller. When working with observational (i.e. non-experimental) data, it is often challenging to establish the existence of causal relationships between interventions and outcomes. Propensity Score Matching (PSM) provides a powerful tool for causal inference with observational data,...Read more about Introduction to Propensity Score Matching with MatchIt
by José Aveldanes. The rise of AI, Machine Learning, and Data Science are harbingers of the need for a significant shift in social science research. Computational Social Science enables us to go beyond traditional methods such as Ordinary Least Squares, which face challenges in addressing...Read more about Computational Social Science in a Social World: Challenges and Opportunities