From Political Science to Gamedev Company: Daniil Kornev on His Studies of Game Analysis and Why Political Scientists Need Python
Daniil Kornev is a 2022 graduate of the Bachelor’s programme 'Political Science and World Politics'. Now, he is studying in the campus master's programme in UX-analytics and working at a gamedev company as a head of data analysis direction. We talked to Daniil about how programming helped political scientists, which thesis topic could help you find a career to your liking and how computer games were related to political science.
— Could you tell us why the programming language Python is useful for political scientists?
— Let's start a little from afar—I'll tell you how I happened to come into the world of programming and working with data. When I was applying for the Bachelor's programme, I could hardly identify as a 'quantitativer' or a programmer though I can't say I was bad at exact sciences. My main focus has always been on research of philosophical theories. It has always seemed to me that a person is capable of searching for objective truth which many modern paradigms deny. That's what happened to me once: I bumped into the fact that objective knowledge, its concept depends on an interpretation, you can hardly measure it with a ruler or sensors.
However, I found something which allowed me to approximate to objective measurement of things with the help of mathematics and statistics—I started working with them in the framework of a minor and a course in quantitative methods. This is how it started and is still continuing up to the present day—due to active work with data, statistics and visualisations, I started using Python as a main work tool more actively. Python happened to be much more flexible than R, more effective in terms of speed and also allowed me not only to conduct research but also put into life complex things such as applications, dashboards and many others.
The answers to the question of why Python can be useful to political scientists may vary. If you are interested in exploring politics, it is one of the best tools. You can analyse more than just boring figures. Your primary data can be texts from interviews, news reports and many other things from which you can extract the most common speech patterns, and contexts, divide authors according to ideas and so on.
Aside from academia, Python and a general understanding of data management principles significantly increase your competitive ability in the labour market. This goes beyond IT. In the modern world, a data management skill and the ability to solve tasks of business or state based on facts (a data-driven approach) are very valuable in every sphere and company which strives to succeed in the market.
Generally, I think that Python is an amazing warm-up for your brain allowing you to pull away from the everyday thinking pattern and learn, on the one hand, to structure your approach to task solving, and, on the other, to master a new useful skill.
Summing up, I would say that programming wouldn't be useful to everyone both in daily life and work or studies—many people have diametrically opposed spheres and aspirations. However, it is definitely worth it to try mastering this skill at least at a basic level.
— In 2022, you graduated from the Bachelor's programme 'Political Science and World Politics'. Could you tell us about your thesis and the results of your research?
— The thesis was an interesting adventure. I have always stuck to the opinion that one should research what they are genuinely interested in and what stirs their curiosity. When the time to choose the thesis topic came, I was thinking for a long time and arrived at the conclusion that I was passionate about computer games, in particular—the differences in political opinions of various game communities' representatives. I couldn't believe at a purely thought-experiment level that people who play 'Tanks', on the one hand, and those who play in the imaginary world with elves and dragons, on the other, do not have any fundamental differences in their political preferences. This is why I decided to sort everything out.
My thesis topic was: 'Political Opinions of Gamers: Correlation between Gameplay Features and Political Attitudes'. Initially, I made a selection of the most popular online games. After that, I tried to break a game into constituent units such as 'existence of stratified systems' (clans and guilds), 'militarisation' of the game process and others. All this decomposition was validated under the supervision of several game designers I knew.
When I was done with the decomposition, I conducted an extensive survey within the community of each researched game where the players answered questions related to their political attitudes.
As a result of combining quantitative research of data from the survey and the interview with the community representatives, I arrived at very curious conclusions: certain game mechanics really attract the audience whose opinions are quite similar on certain political issues. For instance, paramilitary games often attract people whose opinion is close to the so-called power politics; competitive games draw people who believe in free market and individualism.
As a result, I enjoyed the work immensely as I researched something that I genuinely liked and mastered methods of quantitative and qualitative research. Strange as it may seem, I still keep researching games though in a slightly different context.
— You combine teaching, master's studies and work. What programme do you study in and where do you work?
— Now, I am a student of the Master's programme 'UX Analytics and Information System Design'. After the Bachelor's degree, I decided that I wanted to continue my research and future work in the game sphere, and the Master's programme happened to have a separate track devoted to game analytics.
It was still interesting for me to realise how a person perceives such things as games and applications, what drives their choice and preferences—this curiosity is still going, in the first place, it appeared while I was writing my thesis. The direction I chose is a synthesis of knowledge in psychology, programming and statistics. We engage in researching factors describing people's behaviour in applications, websites and any informational systems. On the other hand, we explore more technical issues—the principles of web-services functioning, their algorithms and ways of creation. Now, I've already started writing my master's thesis which is still related to computer games.
As for my work, it is my main focus for now. Before my current workplace, I managed to work in various management research centres, after that, I gradually moved to the sphere of game analytics. Having gained some experience and been in small startups, I embarked upon the search again, and I was hired as an analyst in a quite big gamedev company where I originally engaged in analysing players' behaviour, setting up technical internal analytical processes, and turned the business issues into final research which helped to improve a product. The time was passing, the skills were upgrading, and I happened to become a kind of universal specialist in the analytics world.
Right now, I am a head of data analysis direction, so except for sheer analytics and programming, it often requires advancing managerial skills.
— Could you give advice to those students who want to use the programming languages in the future and quantitative methods in their works?
— Don't be afraid to use unusual approaches. Python with a couple of hours spent on documents and educational videos can help to turn 'another boring work about regression' into a unique research which combines preliminary research of the selection (quantitative data and interview data), appropriate and correct use of statistical tests and, as the cherry on the cake, clear and aesthetically pleasant visualisations of data which can help even those people who are far from quantitative methods to understand your work.
Interview by Veronika Berdnikova, 'Volnaya Redaktsia'