Editing AI for Social Media and Content Moderation (section)

== <span style="color: #FFFFFF;">Remembering</span> ==
* '''Content moderation''' — The practice of monitoring user-generated content on platforms and enforcing community guidelines.
* '''Hate speech detection''' — NLP classification of text that attacks groups based on protected characteristics.
* '''Misinformation detection''' — Identifying false or misleading information; categorized as misinformation (unintentional) or disinformation (intentional).
* '''Spam detection''' — Identifying unsolicited, automated, or low-quality content designed to manipulate platforms.
* '''CSAM (Child Sexual Abuse Material)''' — Illegal content exploiting children; detection is mandatory for platforms under US law (NCMEC).
* '''PhotoDNA''' — Microsoft's system creating perceptual hashes of known CSAM for fast detection; widely deployed.
* '''Deepfake detection''' — Identifying AI-generated synthetic media depicting real people.
* '''Coordinated inauthentic behavior (CIB)''' — Networks of fake accounts working together to manipulate platform algorithms.
* '''Harmful content taxonomy''' — A structured categorization of policy-violating content types across severity levels.
* '''Human review''' — Manual assessment of content by moderators; essential for nuanced cases but causes psychological harm.
* '''Appeal mechanism''' — Process allowing users to contest moderation decisions.
* '''Transparency report''' — Public disclosure by platforms of moderation actions and statistics.
* '''Prevalence''' — The fraction of all content that violates policies; key metric for measuring moderation effectiveness.
* '''Over-removal''' — Incorrectly removing legitimate content; particularly concerning for minority communities.
* '''Under-removal''' — Failing to remove policy-violating content; allows harm to persist.
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