[AK.IPO] GESIS Fall Seminar in Computational Social Science 2023

Do Apr 20 12:11:00 CEST 2023

***Apologies for cross-posting***

Dear colleagues,

We are excited to announce the program of the GESIS Fall Seminar in Computational Social Science 2023: Join us at the GESIS premises in Mannheim from 11 – 29 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 who 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"). Participants can pick from nine week-long courses, including introductory courses on Computational Social Science, Web Data Collection, Big Data Management, or Machine Learning, and more specialized topics such as Automated Image and Video Data Analysis, Deep Learning for Advanced Computational Text Analysis, or Network Analysis. Lectures in each course are complemented by hands-on exercises giving participants the opportunity to apply these methods to data. All courses are held in English.

Week 1 (11 – 15 September)

Introduction to Computational Social Science with R<https://training.gesis.org/?site=pDetails&child=full&pID=0x4693CE99CF9F4C0FB26F47EA79E611BA&subID=0xA28FC9B6141C46659993D16F76CDDC81>

Aleksandra Urman, University of Zurich; Max Pellert, University of Mannheim

Introduction to Computational Social Science with Python<https://training.gesis.org/?site=pDetails&child=full&pID=0x4693CE99CF9F4C0FB26F47EA79E611BA&subID=0x10B7F599A78A430899D69DC39C14F621>

Milena Tsvetkova, London School of Economics; Patrick Gildersleve, London School of Economics

Big Data and Computation for Social Data Science<https://training.gesis.org/?site=pDetails&child=full&pID=0x4693CE99CF9F4C0FB26F47EA79E611BA&subID=0xAD9B75D7B1924EF280EC288984898493>

Akitaka Matsuo, University of Essex; David (Yen-Chieh) Liao, Aarhus University

Week 2 (18 – 22 September)

Automated Web Data Collection with R<https://training.gesis.org/?site=pDetails&child=full&pID=0x4693CE99CF9F4C0FB26F47EA79E611BA&subID=0x72388B266D7A48C98886DFA6C16089BF>

Allison Koh, Hertie School of Governance; Hauke Licht, University of Cologne

Automated Web Data Collection with Python<https://training.gesis.org/?site=pDetails&child=full&pID=0x4693CE99CF9F4C0FB26F47EA79E611BA&subID=0x428CC87C985440C695B86BA777535CB4>

Felix Soldner, GESIS Cologne; Jun Sun, GESIS Cologne; Leon Fröhling, GESIS Cologne

Automated Image and Video Data Analysis with Python<https://training.gesis.org/?site=pDetails&child=full&pID=0x4693CE99CF9F4C0FB26F47EA79E611BA&subID=0x1C221B3409844A5682D4BB6AB53D470D>

Andreu Casas, Vrije Universiteit Amsterdam; Felicia Loecherbach, New York University

Week 3 (25 – 29 September)

Social Network Analysis with R<https://training.gesis.org/?site=pDetails&child=full&pID=0x4693CE99CF9F4C0FB26F47EA79E611BA&subID=0x0E15EE73F46043069631395E0C0190C2>

Michał Bojanowski, Kozminski University and Universitat Autònoma de Barcelona

Introduction to Machine Learning for Text Analysis with Python<https://training.gesis.org/?site=pDetails&child=full&pID=0x4693CE99CF9F4C0FB26F47EA79E611BA&subID=0xCCF089463A984E93A172700D57DA845F>

Damian Trilling, University of Amsterdam; Anne Kroon, University of Amsterdam

From Embeddings to Transformers: Advanced Text Analysis with Python<https://training.gesis.org/?site=pDetails&child=full&pID=0x4693CE99CF9F4C0FB26F47EA79E611BA&subID=0xA07F19FB18CA4F1D8E2DED9DECDE8685>

Hauke Licht, University of Cologne; Jennifer Victoria Scurrell, ETH Zurich

For those without any prior experience in R or Python and those who’d like a refresher, we’re additionally offering two pre-courses, “Introduction to R<https://training.gesis.org/?site=pDetails&child=full&pID=0x6CA4A250062240A1A6BED0FCABC77F76>” and “Introduction to Python<https://training.gesis.org/?site=pDetails&child=full&pID=0x7FEDC6C590644569BB73AC13AE1CD933>” (three 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 that you register 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.

For detailed course descriptions and registration, please visit our website<https://www.gesis.org/en/gesis-training/what-we-offer/fall-seminar-in-computational-social-science> and sign up here<https://training.gesis.org/?query=%20AND%20%20AND%20Fall%20Seminar%20AND%20%20AND%20%20AND%20%20AND%20>!

We also regularly offer courses on computational social science, programming, and digital behavioral data in our workshop program<https://training.gesis.org/?site=pOverview&cat=Workshop> (many of them online). Upcoming workshops, for example, include Advanced R Programming<https://training.gesis.org/?site=pDetails&child=full&pID=0x61D72CBE8F0E439DA97FAC6D072A6447>, Automated Reports & Co with Quarto and Markdown<https://training.gesis.org/?site=pDetails&child=full&pID=0x8298CEAADF6C457B8FBE9EE3FC092E47>, Interactive Data Analysis with Shiny<https://training.gesis.org/?site=pDetails&child=full&pID=0x0D17F8F738B14E0991504DBF8823A002>, and Social Media-Based Field Experiments<https://training.gesis.org/?site=pDetails&child=full&pID=0xACEC1E11C9DB4992BC5E06F3A76AD509>.

Thank you for forwarding this announcement to other interested parties.

Best wishes

The GESIS Fall Seminar team

---

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

-------------- nächster Teil --------------
Ein Dateianhang mit HTML-Daten wurde abgetrennt...
URL: <http://lists.uni-wuppertal.de/pipermail/ipo/attachments/20230420/63b7341e/attachment.html>