13.12.2021
| Inside Data Science |
Michael Windzio on his data-based research in sociology
Michael Windzio addresses the importance of data and its analysis in his research and examines the term “Data Science”.
What topics are you currently working on in your research?
I am working on social networks of adolescents in school classes, in particular on the integration of immigrants into these networks, and on social cohesion and social milieus. Another focus is on global networks of migration and student mobility, and diffusion of education policy. Moreover, I work on juvenile delinquency, adolescents’ gender role orientations, residential relocations of families and residential segregation, and on global educational inequalities.
How important is data to your research?
Data is crucial for my research.
What role does data science play in your research? Do you see yourself more as a user, a method developer, a basic researcher, or perhaps something completely different?
I am still wondering what “Data Science” actually means. Is it limited to Bayesian approaches and machine learning? Or does it also include the standard approach to quantitative analysis in the social sciences? Does it include generalised regression, cross-sectional and longitudinal, as well as econometrics? If so, then data science is at the core of my work.
Anyway, I am definitely a user.
Which data science methods and technologies are in the focus of your research or could also become interesting in the future?
I use longitudinal methods for network analysis, event history analysis (= hazard models), panel regression, multilevel analysis (= mixed models), but also models for causal inference for observational data, such as propensity score matching. In my field, sociology, “computational social science” is rapidly growing, but again, this label is rather vague. But methods of text analysis, such as topic modelling, will certainly become more important also in my work.
What are your main challenges in dealing with data?
I currently do some time-consuming analyses, e.g. a Bayesian model for network evolution over time. Maybe the Data Science Center can provide a better hardware infrastructure to reduce computation time.
And finally, what is your personal motivation for joining the Data Science Center?
It is interesting to see which methods people from other disciplines apply. Hopefully, there will be some dissemination of knowledge, e.g. by workshops on methods we are interested in.
You can learn more about Michael’s activities in his talk
„Global cultures and the world-wide gender gap in education – Fuzzy clusters and multilevel data structures“ in the Data Science Forum on 16.12.2021.
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13.12.2021 | Inside Data Science
Michael Windzio on his data-based research in sociology
Michael Windzio addresses the importance of data and its analysis in his research and examines the term “Data Science”.
What topics are you currently working on in your research?
I am working on social networks of adolescents in school classes, in particular on the integration of immigrants into these networks, and on social cohesion and social milieus. Another focus is on global networks of migration and student mobility, and diffusion of education policy. Moreover, I work on juvenile delinquency, adolescents’ gender role orientations, residential relocations of families and residential segregation, and on global educational inequalities.
How important is data to your research?
Data is crucial for my research.
What role does data science play in your research? Do you see yourself more as a user, a method developer, a basic researcher, or perhaps something completely different?
I am still wondering what “Data Science” actually means. Is it limited to Bayesian approaches and machine learning? Or does it also include the standard approach to quantitative analysis in the social sciences? Does it include generalised regression, cross-sectional and longitudinal, as well as econometrics? If so, then data science is at the core of my work.
Anyway, I am definitely a user.
Which data science methods and technologies are in the focus of your research or could also become interesting in the future?
I use longitudinal methods for network analysis, event history analysis (= hazard models), panel regression, multilevel analysis (= mixed models), but also models for causal inference for observational data, such as propensity score matching. In my field, sociology, “computational social science” is rapidly growing, but again, this label is rather vague. But methods of text analysis, such as topic modelling, will certainly become more important also in my work.
What are your main challenges in dealing with data?
I currently do some time-consuming analyses, e.g. a Bayesian model for network evolution over time. Maybe the Data Science Center can provide a better hardware infrastructure to reduce computation time.
And finally, what is your personal motivation for joining the Data Science Center?
It is interesting to see which methods people from other disciplines apply. Hopefully, there will be some dissemination of knowledge, e.g. by workshops on methods we are interested in.
You can learn more about Michael’s activities in his talk
„Global cultures and the world-wide gender gap in education – Fuzzy clusters and multilevel data structures“ in the Data Science Forum on 16.12.2021.
Interviewee:
Prof. Dr. Michael Windzio
Professor of Sociology of Migration and Urban Research
FB 08 – Sociology
Head of the department „Methods Research“ at SOCIUM
mwindzio@uni-bremen.de
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