Aleksandra Butneva

Research Assistant at the Chair for Quantitative Methods in Social Sciences and the School of Business Informatics

A Warm Academic Welcome

I am delighted to welcome you on my personal website! I am a first-year Master of Science in Cyber Risk Strategy and Governance student at the Bocconi University and Politecnico di Milano. This website is intended for networking and teaching. As I participate in diverse research projects at the University of Mannheim and teach undergraduate- and graduate-level sessions since 2019, research belongs to my key everyday activities. For this reason, I decided to share my teaching and research experience with you.

I taught Empirical Political Research sessions in Fall 2020, so if this area interests you, you can refer to my presentations, affiliated literature, and projects delivered by my students under Publications and Blog Posts. I am open to suggestions and constructive criticism!
For an overview of my (collaborative) research projects at the Collaborative Research Center “Political Economy of Reforms”, The School of Business Informatics, and the MZES (The Mannheim Centre for European Social Research), as well as my independent research, please refer to Projects.
Check out my academic record under CV.

Interests

Quantitative and computational methods in social sciences
Software engineering
Cybersecurity

Education

Bachelor of Arts in Political Science, 2021 (with distinction)
University of Mannheim
Master of Science in Cyber Risk Strategy and Governance, 2023 (in progress)
Bocconi University

Skills

R

90% - Daily Use

Python

40% - Basics, NLP, Pandas, Interactive Plots

Statistics

75%

LateX

95% - Daily use

Git

50%

SQL

25% - Basics

Academic Experience

Data Science Advisory

Prof. Vera Tröger

Sep 2020 – Present Hamburg/Mannheim, Germany

Research Assistant

Mannheim Center for European Social Research (MZES)

May 2020 – Present Mannheim, Germany

Research Assistant

Collaborative Research Center Political Economy of Reforms

Feb 2020 – Present Mannheim, Germany

Teaching Assistant

University of Mannheim, Quantitative Methods

Oct 2019 – Jan 2021 Mannheim, Germany

Awards and Certificates

Scholarship of the EFA – an Interdisciplinary Platform for Science, Politics, Business and Culture

European Forum Alpbach Aug 2020 – Sep 2021

One-year scholarship including free membership

The Society for Political Methodology Jul 2020 – Jul 2021

Test of English as a Foreign Language

TOEFL iBT Sep 2019

Study Scholarship for the best graduates of German Schools abroad

German Academic Exchange Service (DAAD) Sep 2017

Presidential Grant for outstanding academic performance and winner of the German language competition in Russia

Federal Government of Russia Jun 2017

Projects

Healthcare Systems On the Verge of a Digital Revolution

Introducing a Python-based NLP Classifier of medical services in the field of e-health to optimize the interaction among participants of the e-health model

Twitter, Trump, and Coronavirus

Analyzing public sentiment in light of the ongoing pandemic

Judicial Power

Assessing courts' argumentation with data science techniques

Web Presence

An international team of authors developed a computer program for e-health, the Russian Federal Patent Service confirms

NLP - a cutting-edge technology bridging human and computer languages. [RU]

Interview for the myUniMA story - August 2020

Studying in Mannheim Allows Me to Perfectly Combine Research and Student Life [ENG] [DE]

Scholars of The Kazan Innovative Univesity - pioneers of novel scientific developments

Last year, the KIU patented several unique works created by the university scholars and researchers, confirming its reputation as an innovative institution. [RU]

Publications and Blog Posts

Aleksandra Butneva

February 2021 Do salient international events change the substance of issues that are dealt with in constitutional courts?

When is the Supreme Constitutional Court stepping in? Investigating patterns of judicial response in Germany.

Looking into the topic composition and so understanding the material substance of constitutional complaints will, on the one hand, cast a novel perspective on the linkage between Constitutional Courts and public opinion. On the other hand, using international crises as random shocks for causal identification via topic models will extend the methodological pool of tools available for the empirical assessment of reciprocal relationships among citizens, law, and politics.

Aleksandra Butneva, Political Science Students in Fall 2020

December 2020 First steps in coding graphs.

Mankind invented a system to cope with the fact that we are so intrinsically lousy at manipulating numbers. It's called the graph.

The magic of powerful plots.

Aleksandra Butneva, Political Science Students in Fall 2020

November 2020 Writing a good research design.

Communication works for those who work at it.

Beyond research design strategy. Do’s and don’t’s in the academic writing.

Aleksandra Butneva, Political Science Students in Fall 2020

October 2020 Designing experiments in political science as an undergraduate student.

All life is an experiment. The more experiments you make the better.

Living out creativity in political science experiments.

Aleksandra Butneva, Political Science Students in Fall 2020

October 2020 Building good arguments. The science of causality

If you are the effect of it, you caused it.

Causal relationships in social sciences made simple.

Finding appropriate methodology for your undergraduate term paper

Quick and dirty tips for understanding powerful data science methods

Get Academic

Why care?

Building a profound foundation in research methodology is crucial, as only appropriately chosen methods can validate a well-derived theory, which we want to achieve and actively promote in teaching and research. Many undergraduate students are puzzled with the question of how to test their research ideas empirically. In this short presentation one can find common quantitative methods for studying different research questions in PolSci based on Kozuke Imai’s book “Quantitative Social Science” and answer this challenging question for her or himself.

Game Theory

if you expect outcomes of your study to vary (like revolution vs. incumbency preservation) and/ or aim to study the most (un)likely / controversial case; if the actors interact with each other and make decisions conditional on different factors, e.g., coalition talks, portfolio allocation, jury voting, elections, policy decisions.

Topic Models

if you have a lot of (political) text and want to study its content and semantic structure, e.g., wording, argumentation patterns, issues, word frequency. Topic models can summarize and build groups of texts, according to commonalities in written speech, which fosters and enhances the understanding of large text corpora without reading them. You can also predict content conditional on other factors, such as year or author.

Natural Language Processing (NLP)

if you want to dive deeper into computer linguistics (deeper than topic models), check out natural language processing – various methods that allow to fully customize language processing, i.e., you can “tell” the computer how to read and understand your texts (build and train your own linguistic models).

Regression Models

if you are interested in correlation and causality, i.e., how do different factors (independent variables) influence outcomes, check out the classical way of studying PolSci questions. For instance, if you want to know whether party identification of one’s family members directly affects their voting choices, you need to regress the fellow party ID on respondents’ voting preferences. This can be done by using regression models where the expected change in Y is determined by changes in distinct X-s. Depending on where the data about the proposed X-Y relationship comes from (data generation process), researchers can choose functional forms, i.e., how the statistical model will look like.

Panel Data Regression

if your goal is to assess longitudinal trends along different dimensions (e.g., social / political / economic), i.e., observations that are measured repeatedly over time, consider using panel data regression. Implementing time-series modeling makes sense if (1) the same objects/individuals are observed repeatedly (2) multiple variables are measured (3) observations take place at various time points.

Survival Models

if you want to predict the duration / life cycle of a (political) group or union, try out survival models that calculate expected survival of cabinets, political parties, economic unions etc. based on relevant factors that you specify as independent variables. Survival models stem from medicine and were initially used to study the effectiveness of particular treatments and the impact of distinct diseases on patients’ live duration. Same logic was then later applied to assess the survival of significant political unions and so predict political stability.