Both Maria and Minahil are interdisciplinary at heart. They both have a Master’s degree in Social Scientific Data Analysis from Lund University and a Bachelor’s in Political Science and International Relations.
Maria and Minahil have vast knowledge in combining social science theory with quantitative data and analysis methods, and are here to support related research activities. They will also participate in various educational efforts, such as courses or workshops aimed at researchers, in quantitative analysis. When talking about their expertise, they stress various competences.
Maria Lucchetta
- I’ve worked a lot with tools like Python, R, Gephi and NVivo, and I’m comfortable with a range of research methods - whether it’s qualitative, quantitative, or a mix of both. In particular, I am experienced in natural language processing, topic modeling, and sentiment analysis. I can help with designing and carrying out data-driven projects, analyzing data, and presenting the results in a way that’s easy to understand.
Minahil Malik
- My expertise lies in using large language models (LLMs) and advanced machine learning techniques—including text mining and neural networks—to analyze textual data, with a particular focus on political discourse and social media content,. Thus, I specialize in Natural Language Processing (NLP) methods for social science research, web scraping, data wrangling, statistical analysis, data visualization, and pipeline construction for large-scale data processing. Other methodological interests include using Bayesian statistics for the social sciences.
The two research engineers are funded through a collaboration (50/50) between the Methods Centre and the ERC Advanced Grant “PERENNIAL” for one year. After the first year, we hope to continue and even expand the initiative through co-funding with other research projects.
Get in touch to discuss your research ideas
Maria and Minahil have their office space at the Social Sciences Faculty Library in Lund, which forms a hub for the support functions related to research and education. If you want to get in touch with them, explore your ideas or ask for direct support, please write to: RI [at] sam [dot] lu [dot] se (methods-support[at]sam[dot]lu[dot]se) They are very much looking forward to discuss and explore and discuss your research ideas further!