What the Numbers Tell You

Every story on Hacker News comes with key metadata that helps you understand its significance and context. When you retrieve story data through the Needle server, you'll encounter three primary data points: scores, timestamps, and various metadata fields. Understanding these elements is crucial for interpreting the value and relevance of the content you're accessing.

Story Scores Explained

The score represents the number of upvotes a story has received from the Hacker News community, minus any downvotes (though regular users can only downvote comments, not stories). A higher score indicates that more people found the story valuable or interesting enough to upvote it.

Scores provide immediate insight into community reception. A story with 200+ points has resonated significantly with readers, while stories with fewer than 10 points may be niche or newly submitted. When analyzing trends or finding quality content, scores serve as a quick filter for community-validated information.

However, scores should be interpreted alongside submission time. A story posted two hours ago with 50 points is gaining traction much faster than a day-old story with the same score.

Timestamps and Timing

Every story includes a timestamp marking when it was submitted to Hacker News. This data typically appears in Unix timestamp format—the number of seconds since January 1, 1970—though it's often converted to human-readable dates when displayed.

Timestamps are essential for understanding context. Technology news becomes outdated quickly, and a highly-scored story from three years ago may contain information that's no longer relevant. When requesting stories through Needle, always consider the submission time to ensure you're working with appropriately current information.

The relationship between timestamp and score also reveals velocity—how quickly a story is gaining attention. This metric is particularly useful for identifying trending topics or breaking news in real-time.

Additional Metadata

Beyond scores and timestamps, story data includes several other useful fields:

Author information tells you who submitted the story, allowing you to track contributions from specific users or identify submissions from domain experts.

Comment count indicates the level of discussion a story has generated. Sometimes a lower-scored story with extensive comments can be more valuable than a high-scored story with little discussion.

Story type distinguishes between external links, Ask HN posts, Show HN submissions, and job postings, helping you filter for specific content types.

URLs provide the link to the original content, essential for accessing the full article or resource being discussed.

Putting It Together

When analyzing story data through Needle, consider all these elements holistically. A recent story with a climbing score and growing comment count likely represents an emerging trend worth attention, while an older story with a high score and extensive comments may offer deep insights into established topics.