Teaching
The running list of my courses is available at this link with syllabi and evaluations. I am happy to share teaching materials upon request.
Recently I was invited to give a lecture on “Algorithms and Democracy” at the Lecture Series on Digital Transformation of the University of Lucerne. In my lecture I discussed some digital transformation trends and presented some results from my ongoing research. The slides are available here.
Introduction to Text Analysis in R
Workshop (PhD / postdoctoral level), Lucerne University, 2019
General introduction to natural language processing (semantic and bag-of-word approach, building a corpus, text preprocessing, the document-feature matrix). Basic forms of textual data visualization (lexical dispersion and frequency plots). Text modelling (dictionaries, text scaling, statistical topic modeling, structural topic modeling). Advanced topics: elements of scraping (html, regex, working with APIs); mention of Beyond Bag-of-Words: POS tagging and Word Embeddings (Word2vec). Read more
Data Visualization in R
Workshop (PhD / postdoctoral level), Lucerne University, 2019
General introduction to data visualization (defining data visualization and its basic terminology, levels of analysis, univariate graphical summaries, biva-riate graphical summaries). Introducing the Grammar of Graphics and ggplot2 (building up plots of varying complexity through various exercises). Building interactive plots (the plotly package, introducing shiny apps). Read more
Multilevel/Hierarchical Modeling in R
Workshop (PhD / postdoctoral level), Lucerne University, 2019
Multilevel models and data structures (review of linear regression models, recognizing grouped data, costs and benefits of multilevel modeling, con-cept of partial pooling). Fitting linear and generalized linear multilevel models in R (the lme4 pack-age, mixed-models formulas, lmer function, glmer function, varying inter-cepts and varying slopes models, how many groups? Fixed or random ef-fects models?). Bayesian multilevel modeling (motivation, prior and posterior distributions, implementation using RStan). Read more
Research Design in a Quantitative Perspective
Master seminar, Lucerne University, 2019
In this seminar the students are guided through some of the most fundamental social science methods: the comparative, the statistical, and the experimental method. Class discussions develops around the key topics of inference and measurement, to let students appreciate the full potential of quantitative methods for descriptive, predictive and causal inference. Key problems such as endogeneity, measurement error, and selection bias are also presented and discussed. The course includes applied sessions where students can familiarize with statistical methods using R. Read more
Introduction to Data Science in R
Workshop (PhD / postdoctoral level), Lucerne University, 2019
The workshop provides an introduction to R and tidyverse for data science, including using R for data import (readr), wrangling (tidyr, dplyr), visualization (ggplot2), analysis (modelr), and communication (markdown notebooks). Read more
Data Access
MA-level course, University of Milan - DAPS&CO Master program, 2019
The Data Access course instructs students to gather online data: students learn how to handle some of the most common data access situations: scraping information from the Internet, interacting with APIs to get social media data, dealing with JSON and XML files, and show some publicly-available (big) data sets. They will be made aware about the database options available to them – from free software they can install on their laptops up to cloud services suited to handling terabytes of data – and learn their strengths and weaknesses so that they can effectively choose the right database or other storage methodology for different types of research task. Main covered issues: HTML, HTTP protocol (GET, POST), parsing JSON and XML data, CSS and XPath, regexprs, web-based APIs. Read more
Replicable Research and Reporting in R
Graduate School workshop, Lucerne University, 2018
Replication crisis and the importance of replicability in research. Structuring large research projects to achieve full replicability; reporting in R markdown; introduction to using Git and Github. Read more
Advanced Regression Analysis in R
Graduate School workshop, Lucerne University, 2018
Main topics: Generalized Linear Model with linear and nonlinear relations, using Monte Carlo simulations to predict arbitrary quantities of interest. Read more
Replication Seminar: Doing Research, in Practice!
Master seminar, Lucerne University, 2018
The purpose of the seminar is to facilitate the task of students that are keen on developing an empirical project in their Master theses. This seminar is designed to fill the gap between the students’ final works and the classic methods seminars, while offering a service to the scientific community to contrast the replication crisis, by double-checking and re-testing published scientific evidence. Read more
Introduction to R workshop
Graduate School workshop, Lucerne University, 2018
R workshop providing an introduction to the R programming language. Main topics: R operators, data types, functions, control structures, data manipulation (base R and dplyr), basic statistical analysis, elements of more advanced issues (generalized linear model, Bayesian hierarchical modeling, text mining, research replicability). Read more
Comparing Media Systems
Master seminar, Lucerne University, 2018
The purpose of the seminar is to understand the evolution of media systems in the Western world. The seminar traces the change of the media environment from the appearance of the Radio, to broadcast TV, to cable and satellite TV, to the Internet and the spreading of new media. Special attention is devoted to understanding the connections between the media and the formation of citizens’ opinions. Read more
Introduction to R for Data Analysis
Master seminar, Lucerne University, 2018
Luzern Hochschule}Instructor, Master-level workshop ``Introduction to R for Data Analysis’’. R workshop providing an introduction to the R programming language. Main topics: R operators, data types, functions, control structures, data manipulation (base R and dplyr), basic statistical analysis, elements of more advanced issues (generalized linear model, Bayesian hierarchical modeling, text mining, research replicability). Read more
Research Design in a Quantitative Perspective
Master seminar, Lucerne University, 2018
In this seminar the students are guided through some of the most fundamental social science methods: the comparative, the statistical, and the experimental method. Class discussions develops around the key topics of inference and measurement, to let students appreciate the full potential of quantitative methods for descriptive, predictive and causal inference. Key problems such as endogeneity, measurement error, and selection bias are also presented and discussed. The course includes applied sessions where students can familiarize with statistical methods using R. Read more
Introduction to Political Sociology
Master seminar, Lucerne University, 2018
This seminar focuses on the fundamental socio-economic conflicts affecting the development of political systems, encouraging students to reflect on the most salient factors of political change in order to foster their understanding of contemporary social and political divisions. A key concept in the seminar’s discussion is represented by social cleavages. Students are guided through the classic account of cleavage politics (Lipset and Rokkan 1967), in order to understand the fundamental social cleavages in industrial societies, before moving on to the more recent research on political change in post-industrial societies. The last part of the seminar digs into the erosion of the representative function of European party systems and the recent populist uprising. Read more
Introduction to Political Sociology
Master seminar, Lucerne University, 2017
This seminar focuses on the fundamental socio-economic conflicts affecting the development of political systems, encouraging students to reflect on the most salient factors of political change in order to foster their understanding of contemporary social and political divisions. A key concept in the seminar’s discussion is represented by social cleavages. Students are guided through the classic account of cleavage politics (Lipset and Rokkan 1967), in order to understand the fundamental social cleavages in industrial societies, before moving on to the more recent research on political change in post-industrial societies. The last part of the seminar digs into the erosion of the representative function of European party systems and the recent populist uprising. Read more
Research Design in a Quantitative Perspective
Master seminar, Lucerne University, 2017
Co-instructor Prof. Alexander H. Trechsel. Students are guided through the fundamental social science research designs, including the comparative, the statistical, and the experimental method. Class discussions develops around the key topics of inference and measurement, to take students to appreciate the full potential of quantitative methods for descriptive, predictive and causal inference. Key problems such as endogeneity, measurement error, and selection bias are also presented and discussed. The course includes applied sessions where students familiarise with statistical methods using R. Read more
Introduction to Political Communication Research
Master seminar, Lucerne University, 2017
Students are introduced to Political Communication research by replicating in class a selection of recent papers. The substantive contribution of the proposed papers is reviewed in the light of exercises on the replication data, such as replicating the key findings, including extensions and additional robustness tests. In the first part of the seminar, students are offered an introduction to the R programming language and a refresher of regression analysis (linear regression, generalized linear model, multilevel/hierarchical data). One selected paper deals with the experimental design. In the final part, the seminar moves to familiarizing the students with Quantitative Text Analysis: students learn (by doing) how to scrape and analyze political text from various online sources (online newspapers, web pages, social media). Read more