https://paradite.github.io/hn-ratio/

:arrow_up: Hacker News ranked by Comment/Score ratio
https://paradite.github.io/hn-ratio/

d3 hacker-news hn-api hn-ratio score-ratio top-stories

Last synced: 16 days ago
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:arrow_up: Hacker News ranked by Comment/Score ratio

• Host: GitHub
• URL: https://paradite.github.io/hn-ratio/
• Owner: paradite
• License: mit
• Created: 2017-04-21T15:34:28.000Z (about 7 years ago)
• Default Branch: master
• Last Pushed: 2024-04-13T12:03:12.000Z (3 months ago)
• Last Synced: 2024-04-14T11:54:20.693Z (3 months ago)
• Topics: d3, hacker-news, hn-api, hn-ratio, score-ratio, top-stories
• Language: JavaScript
• Homepage: https://paradite.github.io/hn-ratio/
• Size: 11 MB
• Stars: 24
• Watchers: 2
• Forks: 6
• Open Issues: 3
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

Lists

• awesome-hacker-news - HN Ratio

README

        
# HN Ratio

Hacker News top 50 stories ranked by Comment/Score ratio.

## Why

Being a long-time Hacker News reader, I realized that most interesting HN submissions for me are of two categories:

- stories that attract a lot of attention and comments, signaling active and extended debates

- stories that attract a lot of attention but few comments, signaling very insightful post that requires no further comments

Hence, I used the Comment/Score ratio to sort the top HN submissions and locate these stories at the top and the bottom of the list.

## Result

[Web App](https://paradite.github.io/hn-ratio/)

[Raw results by date](https://github.com/paradite/hn-ratio/tree/master/results)

Note that new "promoted" stories with low votes and HN-backed job listings are filtered.

## Why not use HN API in real time?

- It takes some time to get all the data from Hacker News

- HN API does not have archive for top stories in past, whereas I want an archive so that I can find what I missed

Currently I have a GitHub action job that runs daily at 20:00+8 to fetch the top stories. 

## How to run the script

`$ pip install -r requirements.txt`

Then

`$ python hn-ratio.py`

Result for the day will be generated in both json and plain text format (with basic visualization) in the `results` directory.