Abschnittsübersicht

    • The first seminar session will take place on Friday the 13.06.2025 from 10:00(ct) - 16.00 at Seminarpavillon Westend - SP 2.02. It will cover topics 1a - 1c

      On Saturday the 14.06.2025, we will meet for the second session from 10:00(ct) - 16.00 at Seminarhaus SH - SH 2.102 and cover topics 1d - 1f. 

      Please read through the session descriptions in this course and do the pre-tasks before the seminar sessions. 

    • 1a - Intro to Graph Algorithms

      In this session we get to know a fundamental concept of computer science: the graph. What is it? What can we do with it? The answers is algorithms of course, a lot of elegant algorithms, as the ones we will encounter later in this course, run on graphs.

      Please prepare: nothing

    •  1b - Intro to Science and Technology Studies 

      A session to introduce the theoretical framework and scope of Science and Technology Studies. This is an academic field that emerged from a the same space as sociology and specifically examines how knowledge and technological items are influenced by the society that makes them.

      Please prepare:

      Read "The Relevance of Algorithms" by Tarleton Gillespie (fully)
      Write out the proposed structure of tackling algorithms (for future reference) Use our four methods on the text:

      • 🤏 SMMRY: What is this text about? What are the central arguments?
      • 🎭 Affec!: What are your initial emotions reading the text? (any is valid)
      • 1️⃣ 1sent: Which sentence or passage do you want to highlight and why?
      • 🕳️ G_p: What is missing from the text?
    • 1c - Swipe, Match, Stability & Heteronormativity

      In this session, we encounter the »deferred acceptance« algorithm, proposed by Gale and Shapley 1962, famous for matching men and women in heterosexual dating. What social assumptions can we find in the design of this algorithm? 

      please prepare:
      "College Admissions and the Stability of Marriage" by D. Gale and L. S. Shapley

      Use our four methods on the text:

      • 🤏 SMMRY: What is this text about? What are the central arguments?
      • 🎭 Affec!: What are your initial emotions reading the text? (any is valid)
      • 1️⃣ 1sent: Which sentence or passage do you want to highlight and why?
      • 🕳️ G_p: What is missing from the text?
    •  1d - Flow Networks & Social Graphs

      Building upon the previous session we bring the graph to life by looking at our own social networks as graphs. As social network are full of exchange we encounter a new tool from computer science: Flow Networks. We learn about their structure, what algorithms we can use on them and if their results can teach us something new about our social environment.

      please prepare: nothing

    • 1e - Infinite Scroll

      Which algorithms guide us on the platforms we use every day? How do they work and how could they work better for us? We look back on the invention of infinite scroll and towards an apparent future »TikTokization« of social media.

      Please prepare:
      Read "Don't make me think - A Common Sense Approach to Web Usability" by Steve Krug
      read chapter 1 (pp. 10-19) and chapter 4 (pp. 40-43)
      Use our four methods on the text:

      • 🤏 SMMRY: What is this text about? What are the central arguments?
      • 🎭 Affec!: What are your initial emotions reading the text? (any is valid)
      • 1️⃣ 1sent: Which sentence or passage do you want to highlight and why?
      • 🕳️ G_p: What is missing from the text?
    • 1f - You Might Also Like...


      ... this next session: Automatic recommendations can be found everywhere where someone is interested in keeping you on their site a little longer, from online shops to for-you-pages. In this session, we will focus on the use of recommendation algorithms on Social Media platforms, discuss its function for individualization and the common concept of filter bubbles.

      Please prepare: Melville, Prem; Sindhwani, Vikas (2010). "Recommender Systems" (PDF). In Claude Sammut; Geoffrey I. Webb (eds.). Encyclopedia of Machine Learning. Springer. 

      Use our four methods on the text:

      • 🤏 SMMRY: What is this text about? What are the central arguments?
      • 🎭 Affec!: What are your initial emotions reading the text? (any is valid)
      • 1️⃣ 1sent: Which sentence or passage do you want to highlight and why?
      • 🕳️ G_p: What is missing from the text?