From moderation decision to appeal — Non-technical https://thesis.uya.no/proposals/from-moderation-decision-to-appeal/#nontechnical-track BACHELOR Final result: Coded dataset, comparison report and improved explanation template. Task: Check whether official moderation records explain what happened, why it happened and how the decision can be challenged. Data: 120 DSA statements of reasons + six policy pages (public) Select 60 records per platform from the same 30-day period and add each platform’s terms, moderation policy and appeal page. Requires: A second coder for 24 records; no participant recruitment. Method: Code 120 DSA records from two platforms with a fixed checklist. Double-code 24 records and compare missing information by platform and decision type. STEPS Study and improve 1. Read the starting sources and write the exact information problem. 2. Prepare 120 DSA statements of reasons + six policy pages and a separate answer sheet or coding sheet. 3. Run one pilot and fix unclear questions. 4. Collect the named evidence with consent. 5. Group the findings with the stated categories and check the answer sheet. 6. Produce coded dataset, comparison report and improved explanation template. List the three most useful changes. MASTER Final result: A scored record table, an appeal-process diagram and a template for explanations and appeal information. Research question: Explain how automated moderation records distribute responsibility and due process between platforms, reviewers, regulators and users. Research result: A theory-linked model of contestable moderation and evidence-based requirements for explanations and appeals. STEPS Study, compare and explain 1. Read the newest papers and write one exact research question. 2. State which people, cases or documents you will study and what you will compare. 3. Write the selection rules, questions and analysis steps for 240 DSA records + 12 platform policy documents + 8–10 professional walkthroughs. 4. Run one pilot. Fix unclear questions or categories, then keep the guide unchanged. 5. Collect the named interviews, cases or documents with consent. 6. Analyse them with the stated comparison or coding method. Keep disagreements and missing data. 7. Report the answer, the evidence and the practical output named in the assignment. CURRENT PROJECT LITERATURE Automated Transparency: A Legal and Empirical Analysis of the Digital Services Act Transparency Database (2024, peer-reviewed conference paper): https://doi.org/10.1145/3630106.3658970 Provides the closest large-scale audit and identifies discretion and compliance limits in the database. Outside the Black Box: From Algorithmic Transparency to Platform Observability in the Digital Services Act (2024, peer-reviewed journal article): https://ojs.weizenbaum-institut.de/index.php/wjds/article/view/4_2_3 Explains why disclosure must be evaluated by what it lets outsiders observe and scrutinise. IS THEORY STARTING POINTS Are (2024) — Dysfunctional appeals and failures of algorithmic justice: https://doi.org/10.1080/1369118X.2024.2396621 Ground the analysis in observed appeal barriers and perceived procedural justice. Kaushal et al. (2024) — Automated Transparency: https://doi.org/10.1145/3630106.3658970 Use the database audit and its limits as the empirical comparison. Search Scopus or Web of Science and ACM Digital Library using the topic query, then follow citations to the thesis start date. Record searches and compare methods, data, findings and limitations in literature-matrix.csv. Use that review to confirm or revise the gap and choose a current comparator. The linked papers are starting points. PILOT QUESTION When does a platform’s explanation give an outsider enough information to understand and challenge a moderation decision? EXAMPLE TOOLS LibreOffice Calc, Zotero, Taguette or NVivo; no programming required. Equivalent tools are fine. FIRST THREE ACTIONS 1. finalise the four platforms, period, sampling table and 12 policy documents; archive the source files. 2. Pilot the coding guide on 24 records with two coders; revise and finalise the guide before the final sample. 3. Write three fictional walkthrough cases and one fixed appeal task; recruit professionals only after consent and data handling are approved. INTERVIEW QUESTIONS - Can you explain what happened and why from this record alone? - What information would you need before advising an appeal? - Who is responsible for checking or correcting this decision? LITERATURE SEARCH content moderation appeal algorithmic justice DSA statements of reasons contestability platform governance DATA 240 DSA records + 12 platform policy documents + 8–10 professional walkthroughs (mixed) Select 60 records per platform from one fixed period, balanced by decision ground and automation field. Add each platform’s terms, moderation policy and appeal page. Run fictional walkthrough cases with professionals and material free of harmful content. DSA Transparency Database data download: https://transparency.dsa.ec.europa.eu/explore-data/download European Commission DSA database FAQ: https://digital-strategy.ec.europa.eu/en/faqs/dsa-transparency-database-questions-and-answers HOW TO TEST IT Apply a fixed coding guide to all records and double-code 20%. Compare completeness and contestability by platform, ground and automation field. In walkthroughs, ask professionals to explain the decision and choose an appeal step; code missing information, responsibility and due-process concerns. FINAL RESULT A scored record table, an appeal-process diagram and a template for explanations and appeal information. ACCESS OR PEOPLE Recruit 8–10 researchers, regulators, civil-society or prevention professionals; obtain consent and avoid confidential cases. TEMPLATES https://thesis.uya.no/starters/from-moderation-decision-to-appeal/nontechnical/data-plan.csv https://thesis.uya.no/starters/from-moderation-decision-to-appeal/nontechnical/evaluation.csv https://thesis.uya.no/starters/from-moderation-decision-to-appeal/nontechnical/literature-matrix.csv Use participant codes instead of names or email addresses.