HN Explorer

Ask HN: What data visualization about Hacker News would you like to see?

25 points by vivaladav ↗ HN
I have been working for a while on a tool called HN EPLORER, which uses the HN API to acquire data from the website and then process it to do visualization and interactive searches.

Today I acquired all the data from 2017 and I will be soon blogging about it.

I was wondering what kind of charts/stats people would like to see.

Some examples are: - heatmaps showing what times most posts are posted - bars showing which days of the month are more active - word clouds showing most used terms in titles

I am looking for suggestions to expand the visualizations, so let me know if you have any ideas.

For anyone interested in using the tool, check out http://hnexplorer.com

8 comments

[ 3.2 ms ] story [ 32.4 ms ] thread
PaulHoule
I am interested in who the good commenters and the time dependence of certain concepts (for instance there are bursts of activity associated with conventions run by companies like Apple and Amazon, bursts associated with security breaches and issues, etc.)
toomuchtodo
Which days and times are most active for companies using posts for content marketing purposes.

How long YC companies take to find candidates/fill positions for HN job postings (perhaps by how many times you see the same post occur over a window of time). Usually has "(YC {{BATCH}})" in the title, but not always.

Dude2020
Most frequently mentioned keywords that are not common words in the banned posts.
levistoddard
Visualizations around "who is hiring". Which locales trending at various times, Remote vs On-site, number jobs posted, etc.
shortoncash
I'd like a view of the technology keywords on the front page for tech stories. Sort of a buzz metric for things gaining traction and things that are fading away.
ralusek
Sentiment analysis whenever a language is brought up, particularly JavaScript.

Then it would be great to see how many users have a negative sentiment associated with the "ageism" threads on HackerNews, and find a union of the users who fall heavily negative in both threads. All bets on 100% overlap.

yehosef
this would be interesting to me also