ReelCiety Recommendation System Overview

This document provides a high-level overview of how ReelCiety’s recommendation systems operate across feeds, explore surfaces, and suggested content experiences. It is designed to promote transparency, trust, and accountability while safeguarding proprietary technology, platform security, and user safety.

1. Purpose & Scope

ReelCiety’s recommendation systems are responsible for helping users discover relevant, engaging, and safe content across a visual-first social environment. These systems operate at scale and are continuously refined to balance personalization, content diversity, creator opportunity, and harm reduction.

This overview explains the objectives, guiding principles, and governance controls of recommendation systems without disclosing sensitive implementation details that could enable manipulation or abuse.

2. Recommendation Surfaces

Recommendation systems influence multiple areas of the ReelCiety experience, including:

  • Home and explore feeds
  • Suggested posts, reels, and stories
  • Recommended creators and accounts
  • Hashtag and topic discovery
  • Related content suggestions

3. Core Objectives

The primary objectives of ReelCiety’s recommendation systems include:

  • Relevance: Showing content aligned with user interests and context.
  • Safety: Reducing exposure to harmful, abusive, or misleading material.
  • Integrity: Preventing manipulation, spam, and coordinated abuse.
  • Diversity: Supporting a broad range of creators, formats, and viewpoints.
  • Well-being: Avoiding over-amplification of content that may negatively impact users.

4. Inputs & Signals (High-Level)

Recommendation systems may evaluate a wide range of signals, including:

  • User interactions (likes, comments, shares, watch time)
  • Content attributes (format, captions, hashtags, language)
  • Account signals (authenticity, history, enforcement status)
  • Contextual signals (recency, location relevance, device)
  • Safety and quality indicators

No single signal determines ranking or visibility. Signals are evaluated in combination and may change over time as systems are improved.

5. Personalization vs. Global Signals

ReelCiety balances personalized recommendations with broader platform signals:

  • Personalized signals reflect individual user preferences and interactions.
  • Global signals reflect platform-wide trends, safety constraints, and integrity checks.

This balance helps prevent filter bubbles while maintaining relevance.

6. Content Eligibility

Not all content is eligible for recommendation. Content may be excluded or limited if it:

  • Violates Community Guidelines or other policies
  • Is under moderation review or enforcement
  • Contains sensitive or age-restricted material
  • Is associated with spam or manipulation attempts

7. Integrity & Abuse Protections

Recommendation systems incorporate safeguards to detect and mitigate:

  • Artificial engagement and bot activity
  • Coordinated inauthentic behavior
  • Spam networks and content farms
  • Mass reporting or brigading campaigns

Accounts or content engaging in such behavior may experience reduced reach or removal from recommendation surfaces.

8. Sensitive & High-Risk Content

Certain categories of content receive additional scrutiny or distribution limits, including:

  • Self-harm or suicide-related material
  • Graphic violence or disturbing imagery
  • Sexual or adult content
  • Content involving minors
  • Public health or crisis-related information

9. Human Oversight & Review

While recommendation systems rely on automated processes, human teams play a critical role in:

  • Designing policy constraints
  • Reviewing edge cases and escalations
  • Auditing system behavior
  • Responding to regulatory or safety concerns

10. Algorithmic Governance

ReelCiety maintains internal governance frameworks for recommendation systems, including:

  • Risk assessments and impact analysis
  • Testing for unintended bias or harm
  • Regular performance and safety evaluations
  • Documentation and accountability processes

11. User Feedback & Controls

User feedback informs ongoing system improvements. Users can influence recommendations through:

  • Engagement choices
  • Reporting content
  • Blocking or muting accounts
  • Using preference and interest settings

12. Regulatory Alignment

Recommendation systems are designed to align with applicable transparency, consumer protection, and online safety regulations. Adjustments may be implemented to comply with jurisdiction-specific requirements.

13. Changes & Updates

ReelCiety may modify recommendation systems to improve safety, relevance, or compliance. Material changes may be reflected in updated transparency documentation or reports.

14. Contact

Transparency & Integrity: transparency@reelciety.com
Policy & Governance: policy@reelciety.com
Legal & Compliance: legal@nexa-group.org

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