stylometry

Security and privacy

stylometry author attribution

SHOW HN2022

676points
511comments
#25of 2,570 in 2022
Top 1%of 2022 by points

How HN took it

CuriousMostly questions and neutral comments

61 positive, 181 neutral or asking, 3 mixed, 65 critical, out of 310 comments about the project. Thread score +0.00.

Privacy: 1 for, 39 againstPerformance: 20 for, 18 againstIdea: 25 for, 2 againstExecution: 5 for, 4 againstDesign: 4 for, 1 against

The thread, comment by comment

Each row is a top-level comment and its replies, in HN's order. Select a cell to open that comment on HN.

positive neutral or mixed critical about another commenter or something else the maker

What HN said

What people liked

  • Accurately found old alternate accounts for some users

    From 2 comments
    • Wow. This gives a lot of false positives, but it found all ~10 of my old accounts over the years. The most interesting thing is that my writing style changed pretty drastically…
      sillysaurusx on HN
    • Oh wow, it's really sure that I'm stavrosk, which I am: https://stylometry.net/user?username=stavros The next person is 30% less certain, that's huge! This would basically…
      stavros on HN
  • Interesting tool for self reflection on writing tone

    From 1 comment
    • This is a super interesting tool for self reflection. Looking at the top 10 similar accounts to mine, it gives me an arms-length view of how other people probably interpret my…
      drc500free on HN

Objections

  • Creepy and enables deanonymization and loss of anonymity

    From 3 comments
    • After a few tries on boring accounts, I thought to try the account of somebody who was notorious for an incident outside of HN, and had a (deservedly) bad time at HN for a couple…
      jsnell on HN
    • This is an evil website. We won’t have any anonymity soon. The highest match is my years old banned account that I forgot about. Where did you get the data from?
      4qz on HN
    • The scary thing is that once you have this data, finding HN matches for individual targeted users on other sites becomes trivial, even if those sites are harder to scrape. I bet…
      bscphil on HN
  • Many false positives

    From 2 comments
    • Wow. This gives a lot of false positives, but it found all ~10 of my old accounts over the years. The most interesting thing is that my writing style changed pretty drastically…
      sillysaurusx on HN
    • Well now I'm self conscious about my closest match being an 0.34 when so many other people are reporting much closer matches with accounts that aren't alts. Do I write weirdly?
      bhaney on HN

Requests

  • Support for Reddit or other sites

    From 2 comments
    • Anything like this for Reddit? Would translating to other language and back defend against this algorithm?
      SnowHill9902 on HN
    • The scary thing is that once you have this data, finding HN matches for individual targeted users on other sites becomes trivial, even if those sites are harder to scrape. I bet…
      bscphil on HN
  • Show a countermeasure or live feedback while writing

    From 1 comment
    • How about this for countermeasure: As you're typing out a comment the software gives you a list of accounts you're becoming similar to. That way you can adjust your writing as…
      DenisM on HN

Questions

  • What threshold means probably the same person?

    From 1 comment
    • I wonder what's a reasonable threshold for "probably the same person". I've never had an alt on HN, and when I searched myself, it found 3 other users above 0.6, none of whom…
      ufmace on HN
  • Where does the data come from?

    From 1 comment
    • This is an evil website. We won’t have any anonymity soon. The highest match is my years old banned account that I forgot about. Where did you get the data from?
      4qz on HN

Alternatives named

  • Unabomber stylistic analysis by FBI

    From 1 comment
    • This is somewhat similar to how they ended up catching the Unabomber. The FBI were literally at a dead end. They ended up posting one of his letters/manifestos in the paper,…
      rcarr on HN

Category, keywords, summaries and labels on this page were made by AI (Thread Reader v2) and not checked by hand. Each point links to the comments it came from.

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