Which of my HN comments get upvoted?

2 pointssema4hacker3mo ago3 comments

I spend too much time on HN posting comments. I can never predict which will be upvoted, so I tabulated them to see if there was any trend:

  68 points on 1 comment  about Musk vs. OpenAI
  39 points on 1 comment  about private equity
  26 points on 1 comment  about Teamshares
  24 points on 1 comment  about surveillance
  23 points on 1 comment  about project pitch
  19 points on 1 comment  about complicated web pages
  16 points on 1 comment  about fire truck efficiency
  15 points on 2 comments about SQLite, elevator cost
  13 points on 2 comments about AI coding errors, balancing cube
  12 points on 2 comments about domestic garbage, my salary history
  11 points on 4 comments about age of study subjects, Las Vegas Sphere, my tech history (2x)
  10 points on 4 comments about Waymo, pest contractors, YouTube Dewey decimal, burglars
  9 points on 11 comments about productivity, a bad comment, surveillance misuse, TLDR wind turbines, robot litter pick up, human memory, Satoshi, AI authorship, bad businesses, barcode security, my tech history, Windows Cortana
  8 points on  5 comments about SQL, POE Switches, writing quality, dieting, my tech education
  7 points on  5 comments about formatting, anthropomorphizing AI, AI bubble, tech employment vs. income, Pascal
  6 points on  7 comments about ability and available time, influence vs. manipulation, bad customer service, Lisa GUI, satisfaction, recommended books, my salary history
  5 points on  6 comments about network providers, accepting credit cards, web page code, old files, robot litter pick up, abandoning Macintosh
  4 points on 14 comments about: estimating projects, OOP, AI bubble, bad skyscrapers, debugging, UCSD Pascal, anthropomorphizing AI, cheap trucks, aspirin, Unix history, original article age, football centers, waiters, my tech history

 Comments with 3 or fewer points are too many to tabulate.

I see no discernible trend or correlation between subject matter, upvotes, writing quality, whatever.

3 comments

belter3mo ago

Doing data science to understand why strangers are mean to you?

shoo3mo ago

hypothesis: expected upvotes = views of comment thread * probability your comment is read given someone reads the comment thread * probability of upvote given someone read your comment

If you make a "great" comment but the comment thread isn't popular, no/few upvotes

If you make a "great" comment in a really popular thread but it's buried down the comment tree where others are less likely to see it, no/few upvotes

Let's define by "great" comment we mean one that readers of that comment upvote at a high rate.

You'll likely get more votes by making a pretty good comment relatively early in a popular comment thread, at a time of the day when many people are reading HN, rather than an absolutely fantastic comment in some thread that hardly any one reads.

There's path dependence -- if there's two equally "great" comments contributed to a thread, and one is made 30 minutes earlier, it's likely that the earlier one accrues a bunch of votes and sub-threads, secures the best real estate at the top of the thread, and ends up with many more votes than the other one.

These may make it harder to identify if the content or topic is having much impact on the accrued votes.

Could perhaps normalise for that by adding metrics for the number of votes that the submission got, or the total number of votes of all comments in the thread, then see if that can explain some of the variation. Measuring the duration between when the comment thread opened and when the comment was posted could be interesting too.

i hope after enough corrections for topic popularity, time of day, how fast you commented, it becomes clear that your best topic is fire truck efficiency, and we can look forward to frequent comments about fire truck efficiency going forward

pestatije3mo ago

i cannot see the "writing quality" column

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