Analysis of dev.to comment frequency over the lifetime of a post
Peter Kim Frank Aug 17
What / Why
I wanted to take a high-level look at when DEV comments are created relative to the thread they're posted on.
DEV members encounter articles from a variety of sources — their home feed, on-site notifications, social media, search engine queries, etc. I was curious about what percentage of comments were on "fresh" threads, vs. the growing long-tail of articles here on the site.
I don't have much experience with data analysis or even SQL, but it was pretty quick/easy to prepare this high-level report. To simplify matters, I focused only on comments created in August.
Step 1: Grab the
created_at date and article ID for all comments (5400 in total)
Step 2: Grab the
published_at date for all articles grabbed in Step 1
Step 3: Calculate the difference (in days) for
Article Date -
As you might expect, it's heavily front-loaded with a rapid decrease as the article gets older.
I decided to clean up the data, and create a "bucket" for 5-30, and 30+:
- 33% of comments are on articles/threads published that day
- 29% on an article that’s 1 day old
- 9% on an article that’s 2 days old
- 4% for 3 days old
- 3% for 4 days old
- 15% for 5-30 days old
- 7% for 30+ days old
I think it's fairly interesting that 7% of comments are posted on articles that were published at least 30 days prior. The "long tail" of evergreen content serves as a great resource for the broader developer community, and it's great to know that the wonderful content contributed here continues to be enjoyed and discussed even beyond the initial burst of exposure.
Hope you found this interesting!