What is Story Metadata?

When you retrieve stories from Hacker News through the Dialer server, each story comes with rich metadata that helps you understand its context and significance within the community. This data includes scores, timestamps, author information, and other attributes that paint a complete picture of each submission.

Understanding Story Scores

The score represents the number of upvotes a story has received from the Hacker News community, minus any downvotes. This metric reflects how much the community values a particular submission:

• Higher scores generally indicate stories that have resonated strongly with readers
• Scores change dynamically as users continue to vote on stories
• A score of 100+ typically means a story has reached the front page
• Scores above 500 are relatively rare and indicate exceptional community interest

Keep in mind that scores reflect both content quality and timing—stories posted during peak hours may accumulate votes more quickly.

Timestamp Information

Each story includes timing data that helps you understand its lifecycle:

• Submission time: When the story was originally posted to Hacker News
• Timestamps are typically provided in Unix epoch format (seconds since January 1, 1970)
• You can use timestamps to filter recent stories, track when discussions began, or analyze posting patterns

Combining timestamps with scores helps you identify "rising" stories—newer submissions gaining votes quickly—versus established discussions that have accumulated votes over time.

Additional Metadata Fields

Beyond scores and timestamps, story data includes:

• Title: The headline as submitted by the user
• URL: The link to the external article or resource (if applicable)
• Author (by): The Hacker News username of the person who submitted the story
• Number of comments (descendants): Total count of all comments and replies
• Item ID: A unique identifier for each story, used for direct access and comment retrieval
• Type: Indicates whether it's a story, poll, or job posting

Practical Applications

Understanding this metadata enables powerful use cases:

• Trend spotting: Sort stories by score to identify what's capturing attention right now
• Time-based analysis: Filter by timestamp to focus on recent submissions or historical discussions
• Engagement metrics: Compare scores against comment counts to find controversial or deeply discussed topics
• Author tracking: Follow specific contributors by monitoring their submission patterns

By interpreting scores, timestamps, and metadata together, you gain insight into not just what's being discussed on Hacker News, but how the community is responding and engaging with different topics over time.