Research Seminar

2018/2019

Учебный год

ENG

Обучение ведется на английском языке

2

Кредиты

Авторы программы

Григорьев Иван Сергеевич

Декальчук Анна Андреевна

Кто читает:

Департамент политологии и международных отношений

Статус:

Курс обязательный

Когда читается:

3-й курс, 1-4 модуль

Преподаватели

Александров Даниил Александрович

Гилев Алексей Владимирович

Горгадзе Алексей Алексеевич

Иванюшина Валерия Александровна

Турченко Михаил Сергеевич

Чапковский Филипп Игоревич

Course Syllabus

Abstract

The research seminar aims at helping students in their scientific and research activities, by mastering their knowledge in research design formulation, as well as new research methods application. The first part of this course is aimed at both reminding to students the main components of a research design and helping them with elaborating their own research designs with respect to their course works.The second part provides students with the choice of one of the three research methods to be introduced to, which suits the research designs of their term papers the best: (i) Qualitative Comparative Analysis, (ii) Social Network Analysis or (iii) methods related to using texts as data. The third part introduces students to the experimental methods and how they can be used in political science.

Learning Objectives

• Develop students' skills in formulating and justifying their research designs
• Master students' capabilities to develop and implement various research strategies
• Acquaint students with the selected method of research and their applications

Expected Learning Outcomes

• Able to formulate and present results of the research based on the selected method
• Able to interpret the results of the research using the selected method, highlighting its strengths and weaknesses
• Able to perform data collection and preparation for the analysis using the selected research method
• Able to perform empirical data analysis using the selected method
• Able to select and overview scientific literature to characterize a research field
• Compares and characterizes the basic research strategies
• Defines the basic principles and peculiarities of the selected research method
• Develops a research design and research strategy using the selected method
• Enumerates and characterizes the basic elements of research
• Formulates and justifies the research design and its key components

Course Contents

• Topic 1.1. Introduction to the Course
  Content and peculiarities of the course. Refreshing the knowledge from year 1 and 2
• Topic 1.2. Elaborating a Research Question
  Literature Review. Developing a Research Question. Research Design Elements and Research Strategies
• Topic 1.3. Evaluating a Research Design
  Developing an introductory part of the research
• Topic 2.1
  2.1 Introduction: The logic of sets according to Ch. Ragin. Necessary and sufficient conditions. Advantages and assumptions of QCA.; 2.2 Introduction to the Social Network Analysis: Basic terms and principles of the SNA; 2.3 Introduction. Features of text data: Lexicon. Frequency analysis of texts. Zipf's law. Data preparation. Morphological analysis. Stamping and Lemmatization.
• Topic 2.2
  2.1 Boolean Algebra in Comparative Analysis: Boolean algebra, conjunction, disjunction procedures, logical OR and AND. Truth tables. Variables’ presentation.; 2.2 Network theory and applications 1: Personal networks and social capital; elites and power structure; 2.3 Feature engineering: Regular expressions & Text classification: Feature engineering. Prediction of attributes by words and features. Algorithms of classification. Naive Bayes. Regression Models.
• Topic 2.3
  "2.1 The Power of QCA in Political Science (classification, hypotheses): Classifications, hypotheses. Minimization procedures. Causal mechanisms. Using software for QCA. Calibration, the necessity of exogenous criteria. Choosing variables. Working with reminders, controversies and missings; 2.2 Network theory and applications 2: Political networks, social movements and collective action; networks in research, digital networks and social media; 2.3 Identifying Characteristic Words: Loglikelihood, Collocations & PMI, Sentiment analysis: Compares the appearance of a word indifferent collections. LogLikelihood: G-squared. Effect size: Log odds ratio; Co-occurrence. N-grams. Methods for detecting collocations. ―bag of words‖ model. Collocation measure. logDice. Pointwise Mutual Information Of Pairs Of Items (PMI); Automatic text sentiment analysis. Extracting opinions and assessments. Analysis of reviews as a classification problem. Dictionaries of evaluation vocabulary."
• Topic 2.4
  2.1 Testing Hypotheses. A Variety of QCA Techniques: MVQSA, FSQCA.: Calibrating and recalibrating data. Testing Hypotheses. The Variety of Techniques: MVQSA, FSQCA; working with non-dichotomous variables; 2.2 Network in bibliometrics: Using SNA for bibligraphic search and analysis; 2.3 Semantic Networks (LSA): Semantic Networks. Latent semantic analysis (LSA).
• Topic 2.5
  2.1 Fuzzy Sets: Working with fuzzy sets. Measures of Consistency and Coverage. Criticism.; 2.2 Network terminology and metrics - 1: Describing, visualising and analysing networks; 2.3 Topic Modeling (LDA): The operationalization of the "topic" concept as a probability distribution vocabulary. Latent Dirichlet allocation (LDA).
• Topic 2.6
  Presentation of the students' projects
• Topic 3.1 Causal inference and experimental design
  The problem of establishing causality in social science. Rubin causal model. External and internal validity.
• Topic 3.2. Designing online and lab experiments
  Experiments on voting; Cooperation games. Measuring trust and reciprocity experimentally. Studying crime in the lab. Anti-social behavior
• Topic 3.3. Introduction to experiments in R
  Obtaining data from R and some elementary data exploration.
• Topic 3.4. Conducting experiments online and in the lab: practical knowledge
  Randomization between treatments, group composition, between- vs. within-subject designs, belief elicitation
• Topic 3.5. Experimental approaches to data analysis
  Comparing group means. ANOVA, ANCOVA. Analysis of factorial between-subjects design. ANOVA for within-subjects design.

Assessment Elements

• In-class participation
  Participation in seminar workshops and contribution to seminar discussions, based on the mandatory readings.
• Project
  A written group assignment (can be done individually upon request from a student), evaluating students’ progress during the second part of the course. The content of the assignment depends on which track from part 2 is chosen.
• Final Test
  Final examination questions cover the materials of the course and include closed (multiple choice) and open questions with a short answer.

Interim Assessment

• Interim assessment (4 module)
  The cumulative grade is calculated as follows: 65 per cent of in-class participation and 35 per cent of project. The final mark is calculated as follows: 65 per cent of cumulative grade and 35 per cent of the final test grade

Bibliography

Recommended Core Bibliography

• Approaches and methodologies in the social sciences : a pluralist perspective / ed. by Donatella della Porta . (2008). Cambridge [u.a.]: Cambridge University Press. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edswao&AN=edswao.283822104
• Chen, D. L., Schonger, M., & Wickens, C. (2016). oTree—An open-source platform for laboratory, online, and field experiments. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsbas&AN=edsbas.E2EC659C
• Collier, D., & Adcock, R. (2001). Measurement Validity: A Shared Standard for Qualitative and Quantitative Research. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsbas&AN=edsbas.4759268E
• Fu, X., Luo, J.-D., & Boos, M. (2017). Social Network Analysis : Interdisciplinary Approaches and Case Studies. Boca Raton, FL: CRC Press. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=1499393
• Geddes, B. (DE-588)171415787, (DE-576)132211866. (2003). Paradigms and sand castles : theory building and research design in comparative politics / Barbara Geddes. Ann Arbor, Mich.: University of Michigan Press. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edswao&AN=edswao.104638176
• Jason Barabas. (2004). How Deliberation Affects Policy Opinions. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsbas&AN=edsbas.A0C9A969
• Mahoney, J. (2003). Long-Run Development and the Legacy of Colonialism in Spanish America. American Journal of Sociology, 109(1), 50–106. https://doi.org/10.1086/378454
• Nguyen, D., Gravel, R., Trieschnigg, D., & Meder, T. (2013). “How old do you think I am?” A study of language and age in Twitter. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsbas&AN=edsbas.E50BF78
• Ragin, C. C. (2013). The Comparative Method : Moving Beyond Qualitative and Quantitative Strategies. Oakland, California: University of California Press. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=784602
• Silge, J., & Robinson, D. (2017). Text Mining with R : A Tidy Approach (Vol. First edition). Sebastopol, CA: O’Reilly Media. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=nlebk&AN=1533983
• Simon Gächter, & Elke Renner. (2010). The effects of (incentivized) belief elicitation in public goods experiments. Experimental Economics, (3), 364. https://doi.org/10.1007/s10683-010-9246-4

Recommended Additional Bibliography

• Gorgadze Aleksey, & Kolycheva Alina. (n.d.). Mapping Ideas: Semantic Analysis of “Postnauka” Materials. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsclk&AN=edsclk.https%3a%2f%2fcyberleninka.ru%2farticle%2fn%2fmapping-ideas-semantic-analysis-of-postnauka-materials
• Huber, L. M., & Schneider, H. L. (2008). Social Networks : Development, Evaluation and Influence. New York: Nova Science Publishers, Inc. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=311265
• Munzert, S. (2014). Automated Data Collection with R : A Practical Guide to Web Scraping and Text Mining. HobokenChichester, West Sussex, United Kingdom: Wiley. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=878670
• William Q Judge, Stav Fainshmidt, & J Lee Brown III. (2014). Which model of capitalism best delivers both wealth and equality? Journal of International Business Studies, (4), 363. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsrep&AN=edsrep.a.pal.jintbs.v45y2014i4p363.386