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SLOP1276 Applied Algorithmic Romance & Profile OptimizationSemester 1, 2027

Week 2 Tutorial: Platform Architecture and the Elo Hierarchy

Inspect Tinder, Bumble and Hinge disclosures, implement toy Elo and distinguish a visibility hierarchy from an observed measure of attractiveness.

4 March 2027

Inputs

This is the first tutorial; week 1 is lecture-only. Review the boundary example in lecture 1, read the three primary platform descriptions linked in week 2 and open the synthetic census. No completed week 1 lab work is required.

Finish with Your shift at Null Island: the interactive quiz. Six new cases ask you to apply the audit, not copy the worksheet’s numbers. Answer every case before revealing the score and worked explanations. The quiz is practice and carries no course marks.

Follow the 60-minute lecture selection and independent-work plan. Complete the preparation and open the workbook before Thursday. The four blocks below are the entire 90-minute tutorial; use existing lecture or study working for review and refinement. Remaining pack material belongs to the week’s independent study allocation.

90-minute tutorial

  1. 20 minutes — draw the boundary and pipeline (slides 4–16). Trace P1/P2/P3 through Alex’s constraints, then mark retrieval, filters, ordering, exposure and mutual selection. Use lecture 1’s input/observable/hidden distinction. Classify the three source claims and put proprietary weights in the unknown column.
  2. 25 minutes — implement toy Elo (slides 17–27). Test equal-rating win 1216, loss 1184 and K = 64 win 1232 from starting ratings of 1200. Trace a win then loss against 1200 to approximately 1199.26, recomputing the expectation. Add an assumed penalty separately; do not attribute it to a platform.
  3. 25 minutes — audit denominators (slides 37–41). Reproduce active/available/reciprocal totals 300/150/40. Validate row inequalities and recompute reciprocal-to-active after adding 50 missing active profiles to East. State why reciprocal-to-available stays unchanged. Handle a zero denominator explicitly.
  4. 20 minutes — test the hierarchy story and take the quiz (slides 29–36 and 42–43). Use ten minutes with the synthetic exposure cases to compare counts with rates. Change the 600/400 allocation to 500/500 while holding response probabilities fixed. Explain why the first rule preserves a seed advantage, then repair one unsupported claim from the synthesis paragraph. Use the final ten minutes for the six-case quiz: about eight minutes to respond and two to review the explanations after all cases are answered.

Deliverable: Platform audit

Save the boundary map made in this tutorial, a source/claim/unknown table, tested updater and exposure/census calculation log. Annotate changes to the map rather than replacing its uncertainty with confidence. Label the data synthetic and record event definitions, denominator, observation window and allocation assumptions. Use the lecture’s worked answers to review the artefact individually or with a partner.

This audit supplies the report’s population definitions. Week 3 extends its input-provenance rules to photographs.

Interactive quiz · 6 cases · about 8 minutes + 2 to review

Your shift at Null Island

The dashboard wants a victory lap. Check its arithmetic first.

Make a decision in every case, then select Reveal answers. You can change any response before submitting. Scores and explanations stay hidden until the whole quiz is answered.

All profiles, disclosures and numbers here are fictional teaching examples. Practice only: no course marks. Responses stay on this page; reloading starts a fresh attempt.

The cases are readable without JavaScript. Enable JavaScript to navigate, submit your responses and unlock the explanations.

Case 01 / 06The queue jumper

Filter → rank → expose

Alex is free Friday 5–7 pm and has $20 total. This toy pipeline first checks meeting time and cost, then sorts the survivors by score. It displays just one card. Travel is not checked in this example.

Three retrieved fictional cards · all times Friday
CardMeetingTotal costScore
Sol6–6.30 pm$129
Nia8–8.30 pm$810
Rio5.30–6 pm$187

Which card is displayed after this pipeline runs?

Case 02 / 06The black-box bluff

Audit a source claim

An invented platform disclosure says: “We use profile fields and past interactions to order recommendations.” A teammate adds: “So it must use Elo with K = 32.” No code, formula or weights are supplied.

Which entry belongs in your source / claim / unknown table?

Case 03 / 06The rating hotfix

Apply a toy Elo update

Two synthetic profiles start at rating 1400. In one simulated comparison, profile A wins. Use K = 24 and the pre-event ratings; do not add a separate penalty.

Model supplied
E = 1 / (1 + 10^((R_B − R_A) / 400)); R′_A = R_A + K(S − E). A win has S = 1.

What is profile A’s new rating after this one event?

Enter one number. A calculator and your lecture notes are welcome.

Case 04 / 06The vanishing denominator

Repair a population summary

A synthetic census contains 250 active profiles, including 100 available and 30 reciprocally eligible. An import finds 50 more active profiles. None of the added profiles is available or reciprocally eligible. These are nested eligibility counts, not mutual likes.

After the import, what are reciprocal-to-active and reciprocal-to-available, in that order?

Case 05 / 06The dashboard victory lap

Counts, rates and causal claims

A manager sees this synthetic log and announces: “A is the better bio. It got more likes.” The two profiles had different audiences; there was no randomised bio experiment.

One reporting window · at most one like per exposure
ProfileLikesExposures
A36900
B20250

Which correction can the log support?

Case 06 / 06The algorithm crowns itself

Test an exposure-feedback story

In a toy allocator, the profile with more likes today receives 800 exposures tomorrow; the other receives 200. Both profiles have the same assumed response probability, 0.05 per exposure. Today A had 800 exposures and B had 200. Expected likes, rather than sampled counts, drive this exercise.

For one sensitivity run, give tomorrow’s 800 exposures to B and 200 to A while keeping probabilities fixed. What follows?

Answer all 6 cases to unlock your score and the worked explanations.

The spec

Before you finish, check your engineering artefact against these requirements.

Teaching team