DASS at the FSS Open Day
On March 30, the Data Analytics and Social Statistics programme held a series of events as part of an Open Day at the Faculty of Social Sciences. The programme of events assumed a hybrid format and included several presentations by representatives of the master's programme.
Ivan Klimov, academic director of the programme and senior researcher at ANR-Lab, spoke about the features of the programme update and the differences in the name in Russian and English. The fact is that the term 'social statistics' in English has a broader meaning than its direct translation into Russian: it denotes the direction of analyzing human behavior in a social environment using modern statistical methods.
'Social statistics' is a field of research that applies advanced statistical data processing techniques to answer research questions related to various areas of people's lives. Covering design and conduct of research, working with large and complex data sets, and the practical application of the latest advances in statistics to analyze data in the study of social science issues, it provides a better understanding of the surrounding society. 'Social statistics' in Russian is a narrower concept and denotes a system of techniques and methods for collecting, processing and analyzing numerical information about social phenomena and processes in society, as well as work on collecting this data.
To avoid inaccurate interpretation, the programme leaders decided to introduce the term 'applied statistics' into the name of the programme, which is closer to the interpretation in the English version of the title. Applied statistics in a broad sense is the science of applying statistical methods of analysis to solve applied problems in various fields using computer data processing, which is the basis of modern data analysis. Our programme emphasizes methods used in the social sciences.
Irina Pavlova, senior researcher and deputy head of ANR-Lab, spoke about the features of admission to the programme and what documents need to be collected for the portfolio competition. Changes in the curriculum of the master's programme were also presented – several courses were added to the curriculum of the new enrollment year, which provide even more opportunities and flexibility in shaping individual student learning trajectories. There are two specialization tracks available for applicants this year, which will be chosen by students admitted to the programme at the beginning of the academic year. The first track, 'Computational Social and Network Sciences,' is dedicated to the rapidly developing quantitative methods in the social sciences. The international laboratory for applied network analysis ANR-Lab has expertise in the field of network analysis that is unique for Russia, which allows students to learn the application of advanced methodology and best global practices in the field of computational social sciences. The second track, 'Applied Statistics and Data Science,' focuses on advanced methods of mathematical statistics and modern advances in the field of data science for application in the study of socio-economic processes and systems.
Daria Maltseva, head of the International Laboratory for Applied Network Research (ANR-Lab), spoke about how master's students organize their research work. Students in the master's programme can undertake internships in the laboratory, be involved in solving applied problems together with laboratory members during a project seminar and applied laboratory projects, and also engage in fundamental research tasks as laboratory research interns. According to the laboratory's personnel development strategy, after completing a master's degree and entering graduate school, research interns move to positions as junior researchers, and then can move further along the career trajectory of researchers. The connection of the educational programme with the laboratory as a scientific department, which at the same time solves applied research problems, is very important and productive for organizing a successful educational process for students aimed at the practical application of acquired skills. During its existence – this year ANR-Lab celebrates its tenth anniversary – the team has managed to gather around itself a community of talented colleagues, partners, and former graduates who act as teachers and experts of the programme.
Natalia Matveeva, researcher at ANR-Lab, presented the laboratory’s research projects. Unique ANR-Lab projects are available to DASS students, which students can join when writing coursework, completing projects, or preparing a master's thesis. The range of projects is very diverse, allowing the development of skills and knowledge in the fields of applied statistics, computational social sciences, network analysis and data sciences through both academic and commercial projects of the laboratory. ANR-Lab is engaged in both the development and adaptation of methodology for a wide range of analysis of social processes, and research in individual scientific areas, such as: the study of social groups and collectives, the study of science and education, the analysis of economic, financial and political structures, the analysis of social media and the media, trust and satisfaction research and others. More details can be found on the laboratory website.
The second event of the open day programme is the workshop 'How we are all interconnected: basic terms of network analysis.'
During the workshop, Anna Semenova, a junior researcher at ANR-Lab and a graduate student at the Department of Mathematics of the Faculty of Economics and Science at the National Research University Higher School of Economics, and Artem Oganyan, a research assistant at ANR-Lab, introduced the participants of the open day to the basic terms and concepts of network analysis. At the workshop, we looked at the use of network analysis and discussed several networks built on the basis of the Harry Potter dataset (a data set about friendship between the characters of the Harry Potter book series).
Anna introduced the audience to the basic concepts of network analysis, and Artyom demonstrated how to use these concepts using the R environment. In particular, colleagues explained what density, transitivity and reciprocity are in network analysis, what communities are and how to detect them. Participants were also introduced to examples of network graphs from various studies.
At the end of the lesson there was a quiz with small prizes. Participants not only took a fresh look at a well-known book series, but also learned how to explore a variety of communities and networks.
Third event – master class 'Artificial Intelligence Technologies for Scientific Research.'
As part of the master class, Anna Kartasheva, research fellow, and Emil Stashevsky, research assistant at ANR-Lab, conducted a practical review of tools in the field of artificial intelligence for scientific research. Artificial intelligence promises to revolutionize the way scientific research is done. However, significant challenges remain in this nascent field.
The following questions were discussed at the master class:
- Is a digital navigator possible for research planning?
- How deeply has automation penetrated the publishing industry?
- How to deal with unfair use of AI by reviewers?
- When will the creation of specialized educational materials that take into account the individual needs of students be implemented?
One of the interesting facts that was discussed at the master class concerned the use of certain words that can indicate that ChatGPT was used to write the text. Y Combinator founder Paul Graham believes that the use of the fancy word delve (to dig, rummage) increases the likelihood that ChatGPT was used when writing the text. There are several more similar words and expressions, for example, showcase, realm, revolutionize, transformative, buzzing, redefining, embarking, clenched, honed, etc.
A recording of all open day events of our DASS master's program is available in the playlist on the ANR-Lab YouTube channel at the link.
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