Interests

Interests are how you tell Scour what you care about. Add a few topics, and Scour uses semantic matching to find relevant content across thousands of sources.

What Interests Do

Unlike other platforms where clicking one article can flood your feed with a topic, Scour only shows content based on interests you've explicitly added. Your clicks and reactions influence what gets suggested, but only interests you choose to add affect your feed.

This keeps you in control. No more wondering why your feed suddenly changed after clicking on one random article.

Creating Interests

Start by adding 3-5 topics you genuinely want to read about. Interests can range from wide areas to narrow niches:

• Wide topics: "AI" will surface content about machine learning, LLMs, robotics, and more
• Narrow topics: "Rust async runtime internals" will find exactly that
• Personal topics: "Home Cooking" or "Photography" are great too. Scour isn't just for tech or work

Here are some examples of what other users are interested in:

Not sure what to add? Browse popular interests to see what others have found valuable. You can copy any interest with one click.

Feel free to add as many interests as you like. Some users have 500+. Scour automatically diversifies your feed so no single topic dominates.

Using Keywords

Each interest has an optional "keywords" field. Use it to refine or disambiguate:

• Disambiguation: "Rust" with "programming, cargo, crates" clarifies you mean the programming language rather than oxidation
• Narrowing scope: "Cooking" with "Italian, pasta, Mediterranean" focuses your results

Tips for Good Interests

• Labels must be unique — You can't have two interests with the same label. Use distinct names like "AI Research" and "AI Tools" instead of both being "AI".
• Labels appear in your feed — When a post matches your interest, the label shows up below the title. Keep them concise.
• Acronyms work — Use "LLM" as a label with "large language models, GPT, Claude" as keywords.

How Matching Works

Scour uses semantic (meaning-based) matching to compare your interests against articles. This means:

• "Machine Learning" will also find articles about "neural networks" and "deep learning"
• "PyTorch" will find articles about PyTorch even if they don't contain that exact word

On top of semantic matching, keywords provide an additional signal. How much keywords matter depends on the interest's specificity tier (see below). For the full picture of how content gets ranked, see How Ranking Works.

Specificity Tiers

Each interest has a specificity setting that controls how strictly articles must match. You can change it by editing any interest.

• Broad — Matching uses only semantic similarity. Good for wide topics like "Technology" or "Culture" where relevant articles may not mention the topic by name.
• Normal (default) — Semantic matching with a keyword boost. Articles that mention your keywords score higher, but articles can still match without them.
• Specific — Strict matching. Articles that don't mention any of your keywords are penalized. Use this for precise terms like "Rust" or "PostgreSQL" where you only want articles that explicitly discuss the topic.

Scour automatically assigns a specificity when you create an interest, but you can always adjust it. If an interest feels too noisy, try switching it to Specific. If you're missing relevant content, try Broad.

Interest Recommendations

As you use Scour (clicking articles, reacting to posts, subscribing to feeds) the system learns what topics might interest you. You'll see recommendations on your interests page and sometimes while browsing your feed.

Here's what a recommendation looks like:

Accept (+) to add it to your interests, or reject (×) to help Scour learn what you don't want.

Suggest Interests from Your Feeds

If you've subscribed to feeds or uploaded an OPML file, Scour can analyze your subscriptions to suggest interests automatically. This is a quick way to bootstrap your interests, especially if you're migrating from another reader.

Use the "Suggest from my feeds" link on the Interests page to get suggestions based on your current subscriptions. OPML uploads also trigger suggestions automatically.

Still have questions? Or feedback on these docs? Please let me know!