Welcome to NETLAB! We conduct research in computational social science, with an emphasis on the intersections of social network analysis / network science, applied natural language processing, and machine learning. Substantively, our work contributes to environmental social science (e.g. social networks and climate change, the environmental movement, soci-ecological development in the North Atlantic), culture and cognition, knowledge and science (e.g. collective intelligence; integrated social and knowledge networks; diffusion processes for information vs. knowledge, beliefs, and ideas; applications of natural language processing and machine learning to detect concepts, claims, frames, and cognitive schemas). You can find out about some of our publications here, and our software development projects here or on via out GitHub page.
The lab is funded in part by grants from the Social Science and Humanities Research Council of Canada (SSHRC) and an Early Researcher Award from the Ontario Ministry of Research and Innovation awarded to the NETLAB Principal Investigator, Dr. John McLevey.
We are currently collaborating with researchers from other institutions in Canada, the US, the UK, Italy, Luxembourg, Germany, and other countries.
Please contact Dr. John McLevey for more information.
We offer methods workshops. You can read about them here. Our plan is to offer workshops at the University of Waterloo annually (usually in early April) and occasionally at other universities. This year (2020) we are offering two workshops at the University of Waterloo: (1) An Introduction to Social Network Analysis in Python and (2) An Introduction to Automated Text Analysis in Python. Dr McLevey is also teaching a week long class with NETLAB alum Jillian Anderson on "Fundamentals of Data Analysis with Python" at the 49th GESIS Spring Seminar (Digital Behavioral Data) in Cologne, Germany.
Interested in Joining Us?
If you are interested in working in NETLAB or pursing a graduate degree at the University of Waterloo, please send me an email explaining why you are interested in working together and what your educational and / or professional background is. Although there are no open positions right now, there may be in the near future.
- Mar. 19, 2018
Using recordlinkage for classifying candidate record pairs.
- Aug. 29, 2017
Generate and analyze networks with metaknowledge.
- Aug. 29, 2017
Learning how to extract and explore records from raw bibliometric data.