[AK.IPO] GESIS Fall Seminar in Computational Social Science

[Mauk, Marlene]

***Apologies for cross-posting***

Dear colleagues,

We are excited to announce the program of the GESIS Fall Seminar in Computational Social Science 2022: Join us at the new GESIS premises in Mannheim from 05 September to 23 September and choose from a variety of introductory and advanced courses on computational social science methods!

The GESIS Fall Seminar targets social scientists, data scientists, and researchers in the digital humanities that want to collect and analyze data from the web, social media, or digital text archives. Its courses are taught by both GESIS and international experts and cover methods and techniques of working with digital behavioral data ("big data").

Week 1 comprises courses on the foundations of working with digital behavioral data, courses in Week 2 focus on the collection and management of big data, and courses in Week 3 cover different techniques for analyzing these data. Lectures in each course are complemented by hands-on exercises allowing participants to apply these methods to data. All courses are held in English.

Week 1 (05 - 09 September): Foundations of Working with Digital Behavioral Data

Introduction to Computational Social Science with R<https://training.gesis.org/?site=pDetails&child=full&pID=0xB75F899267F14C648AED7D43EBFF3BFB&subID=0xC5DFEAD4963B441EAAE3CFF2D786EEB4>
Dr. Aleksandra Urman, University of Zurich
Dr. Max Pellert, Sony Computer Science Lab Rome

Introduction to Computational Social Science with Python<https://training.gesis.org/?site=pDetails&child=full&pID=0xB75F899267F14C648AED7D43EBFF3BFB&subID=0xD5592250CB29401494092DB4FD3F47B8>
Prof. Dr. Milena Tsvetkova, London School of Economics
Dr. Patrick Gildersleve, London School of Economics

Tools for Efficient Workflows, Smooth Collaboration and Optimized Research Outputs<https://training.gesis.org/?site=pDetails&child=full&pID=0xB75F899267F14C648AED7D43EBFF3BFB&subID=0x0ECFCCE392F64C7281C5FDE598767F2F>
Dr. Julia Schulte-Cloos, University of Munich
Lukas Lehner, University of Oxford

Week 2 (12 - 16 September): Collection and Management of Digital Behavioral Data

Automated Web Data Collection with R<https://training.gesis.org/?site=pDetails&child=full&pID=0xB75F899267F14C648AED7D43EBFF3BFB&subID=0x44757916B99049C88889E388D33CF4EE>
Dr. Theresa Gessler, University of Zurich
Dr. Hauke Licht, University of Cologne

Automated Web Data Collection with Python<https://training.gesis.org/?site=pDetails&child=full&pID=0xB75F899267F14C648AED7D43EBFF3BFB&subID=0xCE318FE52487447889F1ED408284EE3E>
Felix Soldner, GESIS Cologne
Dr. Jun Sun, GESIS Cologne
Leon Fröhling, GESIS Cologne

Big Data Management and Analytics<https://training.gesis.org/?site=pDetails&child=full&pID=0xB75F899267F14C648AED7D43EBFF3BFB&subID=0x11A07CB7FEC34087A37E321F487052E2>
Prof. Dr. Rainer Gemulla, University of Mannheim
Adrian Kochsiek, University of Mannheim

Week 3 (19 - 23 September): Analyzing Digital Behavioral Data

Network Analysis in R<https://training.gesis.org/?site=pDetails&child=full&pID=0xB75F899267F14C648AED7D43EBFF3BFB&subID=0x6CEE7167255343E09662D11A8D5B2E9A>
Dr. David Schoch, GESIS Cologne
TBA

Introduction to Machine Learning for Text Analysis with Python<https://training.gesis.org/?site=pDetails&child=full&pID=0xB75F899267F14C648AED7D43EBFF3BFB&subID=0x1ED0D6BBCDA34A5B931409B7FCF74383>
Prof. Dr. Damian Trilling, University of Amsterdam
Prof. Dr. Anne Kroon, University of Amsterdam

Automated Image and Video Data Analysis with Python<https://training.gesis.org/?site=pDetails&child=full&pID=0xB75F899267F14C648AED7D43EBFF3BFB&subID=0xEA5AB451EFA9478B9744CC9A5E538802>
Prof. Dr. Andreu Casas, Vrije Universiteit Amsterdam
Felicia Loecherbach, Vrije Universiteit Amsterdam

For those without any prior experience in R or Python and those who'd like a refresher, we're additionally offering two pre-courses, "R 101<https://training.gesis.org/?site=pDetails&child=full&pID=0x4E341CAD9705477385B3CD4D03852BE5>" and "Python 101<https://training.gesis.org/?site=pDetails&child=full&pID=0x6E6463C05B444689BD48FF6A8C7329ED>" (two days, online) in the week before the start of the Fall Seminar.

All courses are stand-alone and can be booked separately - feel free to mix and match to build your own personal Fall Seminar experience that perfectly suits your needs and interests. There is no registration deadline, but places are limited and allocated on a first-come, first-served basis. To secure a place in the course(s) of your choice, we strongly recommend registering early.

Thanks to our cooperation with the a.r.t.e.s. Graduate School for the Humanities at the University of Cologne, participants of the GESIS Fall Seminar, can obtain 2 ECTS credit points per one-week course.


Please visit our website<http://www.gesis.org/fallseminar> and sign up here<https://training.gesis.org/?site=pDetails&pID=0xB75F899267F14C648AED7D43EBFF3BFB&lang=en_US> for detailed course descriptions and registration!


For further training opportunities, look at our Summer School in Survey Methodology<https://www.gesis.org/summerschool> and workshop program<https://www.gesis.org/workshops>.

Thank you for forwarding this announcement to other interested parties.

Best wishes and stay healthy
Your GESIS Fall Seminar team

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GESIS - Leibniz-Institute for the Social Sciences
GESIS Fall Seminar in Computational Social Science
email: fallseminar at gesis.org<mailto:fallseminar at gesis.org>
web: www.gesis.org/fallseminar<http://www.gesis.org/fallseminar>
facebook: https://www.facebook.com/GESISTraining
twitter: https://twitter.com/gesistraining


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