News
Registration in the LFS -- action required (if not done already)Written on 06.12.23 by Ingmar Weber If you have not yet registered in the LFS then please email studium@cs.uni-saarland.de with me (= iweber@cs.uni-saarland.de) in CC. Note that you will have to email from your official student email to avoid impersonation. Please do so *today* and by tomorrow at the very latest. This was… Read more If you have not yet registered in the LFS then please email studium@cs.uni-saarland.de with me (= iweber@cs.uni-saarland.de) in CC. Note that you will have to email from your official student email to avoid impersonation. Please do so *today* and by tomorrow at the very latest. This was originally due by Nov 27. |
Reminder: register in the LSF (if not done already)Written on 06.12.23 by Ingmar Weber Dear all, As mentioned in the first two lectures (see e.g. https://docs.google.com/presentation/d/1bSA6H0ZBpcIW7brYfLg89HXIxNFN3-vKVijS6UYMMvA/edit#slide=id.p21) you have to register in the LSF (https://www.lsf.uni-saarland.de/) to eventually obtain credits for the course. This was required by Nov… Read more Dear all, As mentioned in the first two lectures (see e.g. https://docs.google.com/presentation/d/1bSA6H0ZBpcIW7brYfLg89HXIxNFN3-vKVijS6UYMMvA/edit#slide=id.p21) you have to register in the LSF (https://www.lsf.uni-saarland.de/) to eventually obtain credits for the course. This was required by Nov 27, but if you do so *today* then that's still ok with us. Best regards, Ingmar
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Please pick a paper (and date) for your paper presentationWritten on 13.11.23 by Ingmar Weber If you're taking this course as a 7-credit point seminar then please pick a paper and date for the presentation (from the author's perspective) as soon as possible: https://docs.google.com/spreadsheets/d/1OAg1fTx7SaDQSSlbXTUb7whgloVXDHM6JdmC9HVaZaY/edit For this, please leave a comment in the… Read more If you're taking this course as a 7-credit point seminar then please pick a paper and date for the presentation (from the author's perspective) as soon as possible: https://docs.google.com/spreadsheets/d/1OAg1fTx7SaDQSSlbXTUb7whgloVXDHM6JdmC9HVaZaY/edit For this, please leave a comment in the corresponding column, one for the paper and one for the date. Once we have all the dates/presentations selected, we can then have a second round for choosing a paper to discuss/review. That is only possible for papers that are also presented (on the same day). You can ignore this message if you're taking the course as a 5-point pro-seminar instead. |
We'll start at 10am _sharp_ today (Tue, Nov 7)Written on 07.11.23 by Ingmar Weber Please come on time, i.e. by 9.59am today (Tue, Nov 7). We'll have only one our of instruction, followed by some unsupervised group work. Due to scheduling conflicts and illness, only I (Ingmar) will be present today and only for the first hour. |
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Written on 23.10.23 by Annika Hass The seminar will take place on Tue 10-12 am in building E1.7 room 3.23. Start of the course on Oct. 31. Please do not register for the seminar until you have been officially assigned. |
Data and Society
From finding a mate to booking a holiday, our lives are increasingly mediated by online platforms. Digital traces left by these interactions provide opportunities to study societal phenomena while creating challenges around the responsible use of data. In this seminar, students will learn how computational methods and machine learning can be applied to study society through such data.
The first part of the seminar will familiarize students with existing work in computational social science with each week focused on a topic such as “love” or “food” and methods to quantify it. The second part of the seminar will be about projects in which students are asked to quantify a societal phenomenon of their choice using computational methods.
The overall course performance will be based on (i) overall course participation, (ii) assigned paper presentations, (iii) literature review and “project pitch” (prior to in-depth work), (iv) project presentation, and (v) final project reports.
Apart from learning about interdisciplinary research and applications of machine learning, students will also learn research skills such as how to read and discuss papers, how to plan a project, how to present their work, how to write a scientific paper, and how to work in teams.
Students can take this course as either a seminar (7CP) or a proseminar (5CP) or, for students not in computer science, as a course in the “Optionalbereich” (3CP). For the proseminar variant, the load in the literature-based part at the beginning of the course will be reduced, but the project-based part remains. For the Optionalbereich, students can choose between the two parts, also based on their programming experience.
Requirements: The project-based element of the seminar will require some programming and data analysis experience. Beyond that there are no formal requirements, though a desire to engage in interdisciplinary discussions and an interest in studying societal processes is a must.