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<p class="MsoNormal"><span lang="EN-US" style="font-size:9.0pt;font-family:"Source Sans Pro",sans-serif">***Apologies for cross-posting***<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-US" style="font-family:"Source Sans Pro",sans-serif"><o:p> </o:p></span></p>
<p class="MsoNormal"><span lang="EN-US" style="font-size:12.0pt;font-family:"Source Sans Pro",sans-serif">Dear colleagues,<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-US" style="font-size:12.0pt;font-family:"Source Sans Pro",sans-serif"><o:p> </o:p></span></p>
<p class="MsoNormal"><span lang="EN-US" style="font-size:12.0pt;font-family:"Source Sans Pro",sans-serif">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!
<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-US" style="font-size:12.0pt;font-family:"Source Sans Pro",sans-serif"><o:p> </o:p></span></p>
<p class="MsoNormal"><span lang="EN-US" style="font-size:12.0pt;font-family:"Source Sans Pro",sans-serif">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”).
<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-US" style="font-size:12.0pt;font-family:"Source Sans Pro",sans-serif"><o:p> </o:p></span></p>
<p class="MsoNormal"><span lang="EN-US" style="font-size:12.0pt;font-family:"Source Sans Pro",sans-serif">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.<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-US" style="font-size:12.0pt;font-family:"Source Sans Pro",sans-serif"><o:p> </o:p></span></p>
<p class="MsoNormal"><b><span lang="EN-US" style="font-size:12.0pt;font-family:"Source Sans Pro",sans-serif">Week 1 (05 - 09 September): Foundations of Working with Digital Behavioral Data<o:p></o:p></span></b></p>
<p class="MsoNormal"><b><span lang="EN-US" style="font-size:12.0pt;font-family:"Source Sans Pro",sans-serif"><o:p> </o:p></span></b></p>
<p class="MsoNormal"><a href="https://training.gesis.org/?site=pDetails&child=full&pID=0xB75F899267F14C648AED7D43EBFF3BFB&subID=0xC5DFEAD4963B441EAAE3CFF2D786EEB4"><span lang="EN-US" style="font-size:12.0pt;font-family:"Source Sans Pro",sans-serif;color:#E46C0A">Introduction
to Computational Social Science with R</span></a><span lang="EN-US" style="font-size:12.0pt;font-family:"Source Sans Pro",sans-serif;color:#E46C0A"><o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-US" style="font-size:12.0pt;font-family:"Source Sans Pro",sans-serif">Dr. Aleksandra Urman, University of Zurich<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-US" style="font-size:12.0pt;font-family:"Source Sans Pro",sans-serif">Dr. Max Pellert, Sony Computer Science Lab Rome<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-US" style="font-size:12.0pt;font-family:"Source Sans Pro",sans-serif"><o:p> </o:p></span></p>
<p class="MsoNormal"><a href="https://training.gesis.org/?site=pDetails&child=full&pID=0xB75F899267F14C648AED7D43EBFF3BFB&subID=0xD5592250CB29401494092DB4FD3F47B8"><span lang="EN-US" style="font-size:12.0pt;font-family:"Source Sans Pro",sans-serif;color:#E46C0A">Introduction
to Computational Social Science with Python</span></a><span lang="EN-US" style="font-size:12.0pt;font-family:"Source Sans Pro",sans-serif;color:#E46C0A"><o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-US" style="font-size:12.0pt;font-family:"Source Sans Pro",sans-serif">Prof. Dr. Milena Tsvetkova, London School of Economics<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-US" style="font-size:12.0pt;font-family:"Source Sans Pro",sans-serif">Dr. Patrick Gildersleve, London School of Economics<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-US" style="font-size:12.0pt;font-family:"Source Sans Pro",sans-serif"><o:p> </o:p></span></p>
<p class="MsoNormal"><a href="https://training.gesis.org/?site=pDetails&child=full&pID=0xB75F899267F14C648AED7D43EBFF3BFB&subID=0x0ECFCCE392F64C7281C5FDE598767F2F"><span lang="EN-US" style="font-size:12.0pt;font-family:"Source Sans Pro",sans-serif;color:#E46C0A">Tools
for Efficient Workflows, Smooth Collaboration and Optimized Research Outputs</span></a><span lang="EN-US" style="font-size:12.0pt;font-family:"Source Sans Pro",sans-serif;color:#E46C0A"><o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-US" style="font-size:12.0pt;font-family:"Source Sans Pro",sans-serif">Dr. Julia Schulte-Cloos, University of Munich<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-US" style="font-size:12.0pt;font-family:"Source Sans Pro",sans-serif">Lukas Lehner, University of Oxford<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-US" style="font-size:12.0pt;font-family:"Source Sans Pro",sans-serif"><o:p> </o:p></span></p>
<p class="MsoNormal"><b><span lang="EN-US" style="font-size:12.0pt;font-family:"Source Sans Pro",sans-serif">Week 2 (12 - 16 September): Collection and Management of Digital Behavioral Data<o:p></o:p></span></b></p>
<p class="MsoNormal"><b><span lang="EN-US" style="font-size:12.0pt;font-family:"Source Sans Pro",sans-serif"><o:p> </o:p></span></b></p>
<p class="MsoNormal"><a href="https://training.gesis.org/?site=pDetails&child=full&pID=0xB75F899267F14C648AED7D43EBFF3BFB&subID=0x44757916B99049C88889E388D33CF4EE"><span lang="EN-US" style="font-size:12.0pt;font-family:"Source Sans Pro",sans-serif;color:#E46C0A">Automated
Web Data Collection with R</span></a><span lang="EN-US" style="font-size:12.0pt;font-family:"Source Sans Pro",sans-serif;color:#E46C0A"><o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-US" style="font-size:12.0pt;font-family:"Source Sans Pro",sans-serif">Dr. Theresa Gessler, University of Zurich<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-US" style="font-size:12.0pt;font-family:"Source Sans Pro",sans-serif">Dr. Hauke Licht, University of Cologne<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-US" style="font-size:12.0pt;font-family:"Source Sans Pro",sans-serif"><o:p> </o:p></span></p>
<p class="MsoNormal"><a href="https://training.gesis.org/?site=pDetails&child=full&pID=0xB75F899267F14C648AED7D43EBFF3BFB&subID=0xCE318FE52487447889F1ED408284EE3E"><span lang="EN-US" style="font-size:12.0pt;font-family:"Source Sans Pro",sans-serif;color:#E46C0A">Automated
Web Data Collection with Python</span></a><span lang="EN-US" style="font-size:12.0pt;font-family:"Source Sans Pro",sans-serif;color:#E46C0A"><o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-US" style="font-size:12.0pt;font-family:"Source Sans Pro",sans-serif">Felix Soldner, GESIS Cologne<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-US" style="font-size:12.0pt;font-family:"Source Sans Pro",sans-serif">Dr. Jun Sun, GESIS Cologne<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-US" style="font-size:12.0pt;font-family:"Source Sans Pro",sans-serif">Leon Fröhling, GESIS Cologne<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-US" style="font-size:12.0pt;font-family:"Source Sans Pro",sans-serif"><o:p> </o:p></span></p>
<p class="MsoNormal"><a href="https://training.gesis.org/?site=pDetails&child=full&pID=0xB75F899267F14C648AED7D43EBFF3BFB&subID=0x11A07CB7FEC34087A37E321F487052E2"><span lang="EN-US" style="font-size:12.0pt;font-family:"Source Sans Pro",sans-serif;color:#E46C0A">Big
Data Management and Analytics</span></a><span lang="EN-US" style="font-size:12.0pt;font-family:"Source Sans Pro",sans-serif;color:#E46C0A"><o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-US" style="font-size:12.0pt;font-family:"Source Sans Pro",sans-serif">Prof. Dr. Rainer Gemulla, University of Mannheim<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-US" style="font-size:12.0pt;font-family:"Source Sans Pro",sans-serif">Adrian Kochsiek, University of Mannheim<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-US" style="font-size:12.0pt;font-family:"Source Sans Pro",sans-serif"><o:p> </o:p></span></p>
<p class="MsoNormal"><b><span lang="EN-US" style="font-size:12.0pt;font-family:"Source Sans Pro",sans-serif">Week 3 (19 - 23 September): Analyzing Digital Behavioral Data<o:p></o:p></span></b></p>
<p class="MsoNormal"><b><span lang="EN-US" style="font-size:12.0pt;font-family:"Source Sans Pro",sans-serif"><o:p> </o:p></span></b></p>
<p class="MsoNormal"><a href="https://training.gesis.org/?site=pDetails&child=full&pID=0xB75F899267F14C648AED7D43EBFF3BFB&subID=0x6CEE7167255343E09662D11A8D5B2E9A"><span lang="EN-US" style="font-size:12.0pt;font-family:"Source Sans Pro",sans-serif;color:#E46C0A">Network
Analysis in R</span></a><span lang="EN-US" style="font-size:12.0pt;font-family:"Source Sans Pro",sans-serif;color:#E46C0A"><o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-US" style="font-size:12.0pt;font-family:"Source Sans Pro",sans-serif">Dr. David Schoch, GESIS Cologne<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-US" style="font-size:12.0pt;font-family:"Source Sans Pro",sans-serif">TBA<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-US" style="font-size:12.0pt;font-family:"Source Sans Pro",sans-serif"><o:p> </o:p></span></p>
<p class="MsoNormal"><a href="https://training.gesis.org/?site=pDetails&child=full&pID=0xB75F899267F14C648AED7D43EBFF3BFB&subID=0x1ED0D6BBCDA34A5B931409B7FCF74383"><span lang="EN-US" style="font-size:12.0pt;font-family:"Source Sans Pro",sans-serif;color:#E46C0A">Introduction
to Machine Learning for Text Analysis with Python</span></a><span lang="EN-US" style="font-size:12.0pt;font-family:"Source Sans Pro",sans-serif;color:#E46C0A"><o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-US" style="font-size:12.0pt;font-family:"Source Sans Pro",sans-serif">Prof. Dr. Damian Trilling, University of Amsterdam<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-US" style="font-size:12.0pt;font-family:"Source Sans Pro",sans-serif">Prof. Dr. Anne Kroon, University of Amsterdam<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-US" style="font-size:12.0pt;font-family:"Source Sans Pro",sans-serif"><o:p> </o:p></span></p>
<p class="MsoNormal"><a href="https://training.gesis.org/?site=pDetails&child=full&pID=0xB75F899267F14C648AED7D43EBFF3BFB&subID=0xEA5AB451EFA9478B9744CC9A5E538802"><span lang="EN-US" style="font-size:12.0pt;font-family:"Source Sans Pro",sans-serif;color:#E46C0A">Automated
Image and Video Data Analysis with Python</span></a><span lang="EN-US" style="font-size:12.0pt;font-family:"Source Sans Pro",sans-serif;color:#E46C0A"><o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-US" style="font-size:12.0pt;font-family:"Source Sans Pro",sans-serif">Prof. Dr. Andreu Casas, Vrije Universiteit Amsterdam<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-US" style="font-size:12.0pt;font-family:"Source Sans Pro",sans-serif">Felicia Loecherbach, Vrije Universiteit Amsterdam<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-US" style="font-size:12.0pt;font-family:"Source Sans Pro",sans-serif"><o:p> </o:p></span></p>
<p class="MsoNormal"><span lang="EN-US" style="font-size:12.0pt;font-family:"Source Sans Pro",sans-serif">For those without any prior experience in R or Python and those who’d like a refresher, we’re additionally offering two pre-courses, “</span><a href="https://training.gesis.org/?site=pDetails&child=full&pID=0x4E341CAD9705477385B3CD4D03852BE5"><span lang="EN-US" style="font-size:12.0pt;font-family:"Source Sans Pro",sans-serif;color:#E46C0A">R
101</span></a><span lang="EN-US" style="font-size:12.0pt;font-family:"Source Sans Pro",sans-serif">” and “</span><a href="https://training.gesis.org/?site=pDetails&child=full&pID=0x6E6463C05B444689BD48FF6A8C7329ED"><span lang="EN-US" style="font-size:12.0pt;font-family:"Source Sans Pro",sans-serif;color:#E46C0A">Python
101</span></a><span lang="EN-US" style="font-size:12.0pt;font-family:"Source Sans Pro",sans-serif">” (two days, online) in the week before the start of the Fall Seminar.<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-US" style="font-size:12.0pt;font-family:"Source Sans Pro",sans-serif"><o:p> </o:p></span></p>
<p class="MsoNormal"><span lang="EN-US" style="font-size:12.0pt;font-family:"Source Sans Pro",sans-serif">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.
<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-US" style="font-size:12.0pt;font-family:"Source Sans Pro",sans-serif"><o:p> </o:p></span></p>
<p class="MsoNormal"><span lang="EN-US" style="font-size:12.0pt;font-family:"Source Sans Pro",sans-serif">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. <o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-US" style="font-size:12.0pt;font-family:"Source Sans Pro",sans-serif"><o:p> </o:p></span></p>
<p class="MsoNormal"><span lang="EN-US"><o:p> </o:p></span></p>
<p class="MsoNormal"><span lang="EN-US" style="font-size:12.0pt;font-family:"Source Sans Pro",sans-serif">Please visit
</span><a href="http://www.gesis.org/fallseminar"><span lang="EN-US" style="font-size:12.0pt;font-family:"Source Sans Pro",sans-serif;color:#E46C0A">our website</span></a><span lang="EN-US" style="font-size:12.0pt;font-family:"Source Sans Pro",sans-serif">
and sign up </span><a href="https://training.gesis.org/?site=pDetails&pID=0xB75F899267F14C648AED7D43EBFF3BFB&lang=en_US"><span lang="EN-US" style="font-size:12.0pt;font-family:"Source Sans Pro",sans-serif;color:#E46C0A">here</span></a><span class="MsoHyperlink"><span style="color:#E46C0A">
</span></span><span lang="EN-US" style="font-size:12.0pt;font-family:"Source Sans Pro",sans-serif">for detailed course descriptions and registration!<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-US" style="font-size:12.0pt;font-family:"Source Sans Pro",sans-serif"><o:p> </o:p></span></p>
<p class="MsoNormal"><span lang="EN-US"><o:p> </o:p></span></p>
<p class="MsoNormal"><span lang="EN-US" style="font-size:12.0pt;font-family:"Source Sans Pro",sans-serif">For further training opportunities, look at our
</span><a href="https://www.gesis.org/summerschool"><span lang="EN-US" style="font-size:12.0pt;font-family:"Source Sans Pro",sans-serif;color:#E46C0A">Summer School in Survey Methodology</span></a><span lang="EN-US" style="font-size:12.0pt;font-family:"Source Sans Pro",sans-serif">
and </span><a href="https://www.gesis.org/workshops"><span lang="EN-US" style="font-size:12.0pt;font-family:"Source Sans Pro",sans-serif;color:#E46C0A">workshop program</span></a><span lang="EN-US" style="font-size:12.0pt;font-family:"Source Sans Pro",sans-serif">.<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-US" style="font-size:12.0pt;font-family:"Source Sans Pro",sans-serif"><o:p> </o:p></span></p>
<p class="MsoNormal"><span lang="EN-US" style="font-size:12.0pt;font-family:"Source Sans Pro",sans-serif">Thank you for forwarding this announcement to other interested parties.<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-US" style="font-size:12.0pt;font-family:"Source Sans Pro",sans-serif"><o:p> </o:p></span></p>
<p class="MsoNormal"><span lang="EN-US" style="font-size:12.0pt;font-family:"Source Sans Pro",sans-serif">Best wishes and stay healthy
<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-US" style="font-size:12.0pt;font-family:"Source Sans Pro",sans-serif">Your GESIS Fall Seminar team<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-US" style="font-family:"Source Sans Pro",sans-serif"><o:p> </o:p></span></p>
<p class="MsoNormal"><span lang="EN-US" style="font-family:"Source Sans Pro",sans-serif">---<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-US" style="font-family:"Source Sans Pro",sans-serif"><o:p> </o:p></span></p>
<p class="MsoNormal"><span lang="EN-US" style="font-family:"Source Sans Pro",sans-serif">GESIS – Leibniz-Institute for the Social Sciences<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-US" style="font-family:"Source Sans Pro",sans-serif">GESIS Fall Seminar in Computational Social Science<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-US" style="font-family:"Source Sans Pro",sans-serif">email:
</span><a href="mailto:fallseminar@gesis.org"><span lang="EN-US" style="font-family:"Source Sans Pro",sans-serif;color:#E46C0A">fallseminar@gesis.org</span></a><span style="font-family:"Source Sans Pro",sans-serif;color:#E46C0A">
</span><span lang="EN-US" style="font-family:"Source Sans Pro",sans-serif"><o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-US" style="font-family:"Source Sans Pro",sans-serif">web:
</span><a href="http://www.gesis.org/fallseminar"><span lang="EN-US" style="font-family:"Source Sans Pro",sans-serif;color:#E46C0A">www.gesis.org/fallseminar</span></a><span lang="EN-US" style="font-family:"Source Sans Pro",sans-serif"><o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-US" style="font-family:"Source Sans Pro",sans-serif">facebook:
</span><a href="https://www.facebook.com/GESISTraining"><span lang="EN-US" style="font-family:"Source Sans Pro",sans-serif;color:#E46C0A">https://www.facebook.com/GESISTraining</span></a><span lang="EN-US" style="font-family:"Source Sans Pro",sans-serif;color:#E46C0A"><o:p></o:p></span></p>
<p class="MsoNormal"><span style="font-family:"Source Sans Pro",sans-serif">twitter:
</span><a href="https://twitter.com/gesistraining"><span style="font-family:"Source Sans Pro",sans-serif;color:#E46C0A">https://twitter.com/gesistraining</span></a><span style="font-family:"Source Sans Pro",sans-serif"><o:p></o:p></span></p>
<p class="MsoNormal"><span style="font-family:"Source Sans Pro",sans-serif;color:#E46C0A"><o:p> </o:p></span></p>
<p class="MsoNormal"><o:p> </o:p></p>
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