SICSS-Zurich will take place online from June 14 to June 18, 2021.
We will use this GitHub repo to share Zurich-specific information with you. Please also consult the official website for our site.
Questions/comments? Join us on our Slack channel.
Please fill out our onboarding survey: takes 2min max and greatly helps all SICSS organizers 🙃
As in past years, we recommend some pre-event preparation (reading, coding exercises). These preparations are not meant to be burdensome. We have found that they lead to a richer event. We are happy to help you with your preparations (see office hours below).
Recommended readings (this list will be updated over time):
- Python for Economists, by Ewen Gallic
- Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems, by Aurelien Geron
The days will be organized around topics, with one broad topic per day:
- Day 1: Introduction to statistical learning
- Day 2: Scraping and APIs
- Day 3: Classification and regression
- Day 4: Text as data
- Day 5: Images as data
Time-wise, we will go about the days as follows:
- 09:30-12:00: Teaching input
- 12:00-13:00: Individual lunch breaks
- 13:00-16:00: Independent work in groups
- 16:00-17:30: Wrap up; depending on the day it might start only at 16:30 (but it won't last longer than 17:30)
Important: on Monday, we will start at 09:30 instead of 10:00.
This is the Zoom link for our meetings.
Along the way, there will be some input by guest speakers and lectures from the main venue in Princeton.
You can find all the videos from Princeton here. Note that there are some differences between sites. Hence, it is up to you if you want to watch videos that repeat our material or if you prefer those with different content. In any case, we encourage you to check out as many Princeton videos as possible to profit from the entire SICSS universe 🌠
- 09:30-10:30: Introduction to SICSS, participant presentation (who and where are you? what do you hope to get from SICSS?)
- 10:30-11:00: Coffee break (we will spend it together on Zoom getting to know each other)
- 11:30-12:30: Teaching input: Introduction to statistical learning
- 12:30-13:30: Individual lunch breaks
- 13:30-14:00: Launch Jupyter notebook, Python basics (pandas, matplotlib) -- optional
- 14:00-17:00: Malka and Philine available on Zoom to help you getting started with Python/Jupyter -- optional, just drop in as needed
- 17:00-17:30: Wrap-up
There are no participant presentations on Monday. Instead, the goal of the day is for everyone to be set up comfortably with Python.
- 09:30-10:30: Teaching input: scraping and APIs
- 10:30-11:00: Coffee break (opt-in if you want to spend it in a breakout room)
- 11:00-12:00: Teaching input: scraping and APIs; discussion of tasks for the afternoon
- 12:00-13:00: Individual lunch breaks
- 13:00-16:00: Work in groups
- 16:00-17:00: Wrap-up, group presentations
- 09:30-10:30: Teaching input: Classification and regression
- 10:30-11:00: Coffee break
- 11:00-12:00: Teaching input: Classification and regression; discussion of tasks for the afternoon
- 12:00-13:00: Individual lunch breaks
- 13:00-16:00: Work in groups
- 16:00-17:00: Wrap-up, group presentations
- 09:30-10:30: Teaching input: Text as Data
- 10:30-11:00: Coffee break
- 11:00-12:00: Teaching input: Text as data
- 12:00-13:00: Individual lunch breaks
- 13:00-16:00: Work in groups
- 17:15-18:15: Wrap-up, group presentations
- 09:30-10:30: Teaching input: Images as Data
- 10:30-11:00: Coffee break
- 11:00-12:00: Teaching input: Images as data
- 12:00-13:00: Individual lunch breaks
- 13:00-16:00: Work in groups
- 16:00-17:00: Wrap-up, group presentations
Usually (pre-COVID), the SICSS consists of a series of locally hosted in-person events around the world that are connected to each other by online lectures. To make SICSS as worthwile as possible, even in the absence of locally hosted events, the parent location in Princeton coordinates a SICSS festival. It is an online festival with different events around computational social science. The program is continuously updated here: https://sicss.io/festival.
Samson is a research associate in a project on West African English on the Move at the English Department of the University of Freiburg, and an Adjunct lecturer at the Catholic University of Applied Sciences, Freiburg, where he teaches social and educational work with refugees. Samson’s work on migration and language study inspired his current research on the relationship between language and forms of discrimination. His research concentration straddles his current interest in studying language and discrimination and his previous research on democratization study. Samson received a PhD in Sociology at the University of Freiburg, and he is keen on applying natural language processing in the study of language and discrimination.
Alberto Barradas Chacón is currently a doctoral candidate and university assistant at the Institute for Neuro Engineering, at the Technische Universität Graz, under the supervision of Prof. Selina Wriessnegger. He studied a Bachelor in Science in Computational Systems Engineering at the University of Guanajuato, Mexico, and a Science Masters in Data Analysis at the University of Hildesheim, Germany. Alberto focuses on Behavioural Data Analysis, and his current research topic uses tools and models from affective computing to relate behaviour to their neurophysiological basis with the help of Brain Computer Interfaces (BCI).
Ivo is a PhD student in Political Science at the University of Zurich and a member of the University of Zurich's Digital Democracy Lab. His research focuses affective polarization in multi-party systems; his wider research interests include European far-right politics, political violence and terrorism, natural language processing, quantitative text analysis, and computational social science methods.
Piera Bello is a postdoctoral fellow at the University of Zurich. She received her PhD from the Università della Svizzera italiana (USI). Before joining the University of Zurich, she worked as a postdoctoral fellow at University College London and Ca' Foscari University of Venice. Her primary research interests are in gender economics, pension economics and political economy. Her recent papers investigate the functioning of annuity markets.
Nicolai Berk is a PhD Candidate at the Dynamics Research Training Group and the Chair of Comparative Politics at the Humboldt University Berlin. His main interest revolves around political communication and its effects on elites' and voters' cognitive representations of politics. To study this topic, he combines computational text analysis and econometric tools.
Dweepobotee Brahma is a Fellow at the National Institute of Public Finance and Policy at New Delhi, India where she works on health financing. Previously, she was an Associate Fellow at the Brookings Institution India Center – an affiliate of the Brookings Institution D.C. Her research lies in the intersection of applied econometrics – including causal inference and modern Machine Learning techniques – and development and health economics. She received her Ph.D. in Applied Economics from Western Michigan University in 2019. Her dissertation “Essays in the Application of Machine Learning in Development Economics” looked at India’s progress towards the Sustainable Development Goals in child health using Machine Learning tools.
Jorge de la Cal Medina is a master's student in Economics and Data Science in his last year and a research assistant in econometrics both at the University of Zürich. Computational methods in general are gaining ground in econometric research, but he would like to emphasize especially the computational tools of Causal Science for causal analysis in Econometrics.
Janina Grabs is a postdoctoral associate in ETH Zurich’s Environmental Policy Lab and incoming Assistant Professor of Business and Society at ESADE Business School (Barcelona). Her work studies the implementation and effectiveness of private sustainability governance in agricultural commodity production, and uses both qualitative and quantitative methods. Janina received her PhD in Political Science in 2018 from the University of Münster, and holds a double MSc in Agricultural Economics and Business and Economics from Bonn University and the Swedish Agricultural University (SLU) and a BA in Political Science from McGill University. She also held visiting researcher positions at Carleton University and Yale University.
Simon Happersberger is a PhD researcher in Political Science at the Brussels School of Governance. His research focuses on the comparative effectiveness of EU policy instruments fostering sustainable trade. In particular, he is interested how natural language processing can contribute to political economy research in regard to the nexus of environmental law, environmental politics and environmental economics.
Till received his PhD in sociology from Yale University in 2019 and is a postdoctoral researcher at Bremen University, SOCIUM – Research Center on Inequality and Social Policy, Germany. He is a faculty fellow at Yale University’s Center for Cultural Sociology. His research interests include justice orientations, social memory, post-1989 transformations, and computational social science. As a member of the Working Group on the Comparative Study of Societies at the SOCIUM, he is researching popular beliefs about inequality and wealth. He is interested, in particular, in text as data, social network analysis, and data visualisation, and in how we can use these methods for the analysis of culture and inequality.
Jarek is an assistant professor at Leiden University. He obtained his PhD within the European Doctorate in Law & Economics from the University of Hamburg, Erasmus University Rotterdam, and the University of Bologna. His works on topics related to political economy, institutional economics, environmental politics, and economics, and empirical legal studies.
Maël is a political scientist at the University of Zurich he started working as Developer for the Digital Democracy Lab in the summer 2019. In addition, he is a doctoral student at the Department of Political Science since the beginning of 2021, where he is involved in the research project: "Problem Definition in the Digital Democracy". He is familiar with different programming languages such as R, HTML, CSS, Bash and more and his research focuses on the challenges, implications, and dynamics of digital technologies on democracy as well as computational social science.
I am a PhD candidate in the Environmental Policy Lab at ETH Zürich with an interdisciplinary background, having previously studied social anthropology, geography and environmental science. My research investigates the relationship between land use, livelihoods and global supply chains, with a specific focus on the effectiveness and equity of zero deforestation initiatives in the cattle sector of the Brazilian Amazon. To understand these issues, I primarily use econometric and network analysis approaches to analyse data that is either remotely sensed or collected from the field. However, I am increasingly drawn towards data science techniques, such as web scraping and machine learning and am excited to learn more through the SICSS!
Hauke is a PhD student at the University of Zurich, Department of Political Science. He studies how electoral competition shapes political discourse and he is interested in the role that rhetoric strategies play in democratic representation more generally. In his research, he develops and applies text-as-data and natural language processing methods to address these questions.
Javier Martínez-Cantó is a post-doctoral researcher in the research group on Comparative Politics at the University of Konstanz. Before, he developed his doctorate at the University of Bamberg. His research interests are party organization, legislative behavior and multi-level politics. In his research, he seek to understand how political parties make decisions, and how these influence the behavior of rank-and-file members, legislators and party elites.
Karl Overdick is a Ph.D. student in Management at the Saïd Business School of the University of Oxford. He works on topics in Behavioural and Happiness Economics. He is interested in bringing new computational methods of data acquisition, processing and evaluation to research questions.
Anna is an MA Economics student at Central European University in Vienna. She obtained her undergraduate degree in Economics from Higher School of Economics in Moscow. She is interested in applied microeconomics, public and labour economics.
Tuhina is a Senior Researcher at the King George's Medical University, Lucknow, India. She has a Masters and a PhD in Social Work. Her research interests include disease prevention, social determinants of health, maternal and child nutrition, health communication and health-seeking behaviour. She is interested in the use of computational social science and mixed-methods for investigating public perceptions of health, studying network-related dimensions of health phenomena and monitoring of illness. She also intends to study the realms of health communication, social networks and information-spreading. Her previous research has been published in indexed, peer-reviewed medical/public health journals like WHO bulletin, PLOS ONE, clinical epidemiology and global health, Journal of Tropical Pediatrics and BMJ Open.
Matthias is pursuing a PhD in Economics at the University of St. Gallen. His research interests cover the empirical exploration of a range of questions surrounding adaption of green technologies, covert environmental policy lobbying through media advertisements, and the spread of conspiracy theories via the internet. He holds an MPhil in Economics from the University of Oxford, and a BSc in Economics from the University of Bern.
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