Xikipedia: A Privacy-First Social Feed Built on Wikipedia's Simplicity

A developer has created Xikipedia, a web-based social media feed that uses Simple Wikipedia articles as content and demonstrates how algorithmic curation can work without collecting user data or relying on machine learning.

The project, built by rebane2001, positions itself as both a functional tool and a proof-of-concept about privacy-preserving content recommendation systems. Unlike traditional social media platforms that track user behavior across the web and build detailed profiles, Xikipedia runs entirely in the user's browser with no data collection or sharing.

How It Works

Xikipedia presents users with a feed of content sourced from Simple Wikipedia, the simplified-English version of Wikipedia designed for easier reading. Users can select from predefined categories including Nature, Science, Animals, Anthropology, Places, Sociology, Art, Mathematics, Games, Technology, Music, and Human Sexuality, or create their own custom categories.

The algorithmic component learns from user engagement patterns to suggest similar content. According to the creator, this demonstrates how even basic non-machine learning algorithms can quickly adapt to user preferences without requiring data from other users or building comprehensive user profiles.

Privacy-First Design

The privacy architecture is straightforward: all processing happens locally in the browser, and no data persists beyond the current session. Refreshing the page or closing the tab wipes all algorithmic learning and user interaction data. This approach directly challenges the business model of major social platforms that depend on persistent user data for targeted advertising.

Content Considerations

The use of Wikipedia as a content source means the feed can include articles on any topic covered by the encyclopedia. The creator explicitly warns that users may encounter NSFW content since Wikipedia includes articles on human sexuality and other mature topics. The platform requires users to confirm they are adults before proceeding.

Technical Implementation

The project is open source, with source code available on GitHub. The developer has also established discussion channels on federated social platforms including Mastodon (fedi), Bluesky, and Twitter, suggesting an interest in engaging with communities that value decentralization and privacy.

Broader Implications

Xikipedia represents an interesting experiment in alternative social media design. By using freely available educational content and running entirely client-side, it demonstrates that personalized content feeds don't necessarily require the surveillance infrastructure that characterizes mainstream social platforms.

The project raises questions about whether similar approaches could be applied to other types of content and whether users would accept the trade-off of potentially less relevant content in exchange for complete privacy.

Access and Availability

The platform is accessible through a web interface, with content loading progressively (the demo shows 4% of a 40MB content load). Users can immediately begin interacting with the feed after selecting categories or adding their own.

For developers interested in the technical implementation or users wanting to examine the code, the GitHub repository provides full access to the source. The federated discussion channels offer spaces for community feedback and potential collaboration.

Xikipedia stands as a reminder that alternative approaches to content curation exist, and that privacy-focused design doesn't necessarily mean sacrificing the benefits of algorithmic personalization.