fair_cyberbullying_detection
importedsoftware/fair-cyberbullying-detection
Source code and models for the paper "Cyberbullying Detection with Fairness Constraints". IEEE Internet Computing, 2020
Machine-generated from the listed sources and not yet reviewed by a human.
- Category
- Software & Systems
- Subcategory
- unknown
- License
- MIT(osi)
- Status
- dormant
- Maturity
- deployed
- Organization
- unknown
- Country
- unknown
- Documentation
- unknown
- Tags
- algorithmic-fairness · constrained-optimization · cyberbullying · cyberbullying-detection · deep-learning · ethical-artificial-intelligence · fairness · health-informatics
- Regulatory
- unknown
Top contributors by commit count, from the project’s public repository. Avatars are served by their origin, not stored here. To be removed from this list, open an issue.
Computed from shared tags, weighted so a rare tag counts for more than a common one. These are suggestions, not curated relationships.
- shortcut-ood-fairnessalgorithmic-fairness · fairness
[Nature Medicine] The Limits of Fair Medical Imaging AI In Real-World Generalization
- biomedical-signal-forensics-labalgorithmic-fairness
An open-source toolkit for auditing wearable physiological signals: signal quality, algorithmic fairness, causal sensitivity, and downstream-task impact.
- BiasEval-LLM-MentalHealthfairness
Unveiling and Mitigating Bias in Mental Health Analysis with Large Language Models
- Fair-Codefairness
Auditing algorithmic bias in criminal justice, hiring, lending, healthcare, welfare, and tenant screening: 7 open-source audits, measurable fairness gaps, and concrete fixes.
- abouthealth-informatics
:dizzy: About
- acq-toolshealth-informatics
Toolkit for analyzing physiologic data collected via Biopac AcqKnowledge software.
- api.github.com/repos/ogencoglu/fair_cyberbullying_detectionretrieved 2026-08-05 · via github-api
Machine-imported from GitHub search. Last push 2023-03-25, 21 stars, license reported as MIT. Category and schematic were assigned by keyword heuristics and are unreviewed.
Not yet verified by a human. Correct this record →
/v1/entries/57.json→ .entries["fair-cyberbullying-detection"]
Entries are sharded 64 ways by a stable hash of the id, so a consumer can find any record without an index.