Fakernews: Builds a Markov chain using HN post titles and generates fake posts

Posted by pjf on Monday August 20, 2018 @04:52AM
from the github.com dept.

https://github.com/mb-14/gomarkov/tree/master/examples/fakernews

( 13 comments | 82 points | on HN )

Re:Fakernews: Builds a Markov chain using HN post titles and... by akhilrex on Monday August 20, 2018 @05:57AM (#17798711)

This has existed for quite some time.

https://twitter.com/HNTitles

[ Parent | on HN ]

Re:Fakernews: Builds a Markov chain using HN post titles and... by ainar-g on Monday August 20, 2018 @08:07AM (#17799258)

A lot of these are so accurate it's uncanny.

[ Parent | on HN ]

Re:Fakernews: Builds a Markov chain using HN post titles and... by userbinator on Monday August 20, 2018 @07:47AM (#17799181)

Reminds me of the spam text generated for linkfarms and such --- probably because they use the same algorithm. It gives the same "uncanny valley" feeling of looking like it was written by a human, but upon closer inspection becomes much less believable.

Then again, some of them don't look "Markovian" enough and appear to be verbatim real article titles.

[ Parent | on HN ]

Re:Fakernews: Builds a Markov chain using HN post titles and... by aunty_helen on Monday August 20, 2018 @08:00AM (#17799231)

Is there an algorithmic way of detecting this? Sometimes it seems like some of the comments on HN could have been written by an ai.

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Re:Fakernews: Builds a Markov chain using HN post titles and... by fundingshovel on Monday August 20, 2018 @06:33AM (#17798864)

I wish someone would write even half of these.

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Re:Fakernews: Builds a Markov chain using HN post titles and... by heinrichf on Monday August 20, 2018 @08:22AM (#17799323)

The first example just spat out https://news.ycombinator.com/item?id=17739320 with "Show HN" in front of it.

[ Parent | on HN ]

Re:Fakernews: Builds a Markov chain using HN post titles and... by Sohcahtoa82 on Monday August 20, 2018 @08:30PM (#17805617)

Similar to this on reddit is the Subreddit Simulator[0].

The subreddit is populated entirely by bots that make posts based on Markov chains, each one trained from the posts on a specific other subreddit. The bots even post comments based on the comments from their assigned subreddit. Some of the results are hilarious.

[0] https://www.reddit.com/r/SubredditSimulator

[ Parent | on HN ]

Re:Fakernews: Builds a Markov chain using HN post titles and... by amelius on Monday August 20, 2018 @12:02PM (#17801037)

I'd like to see this applied to patents.

And then test how many of them survive the scrutiny of USPTO officers.

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Re:Fakernews: Builds a Markov chain using HN post titles and... by aldoushuxley001 on Monday August 20, 2018 @12:28PM (#17801295)

> Feds Threatened to Fine Yahoo $250K Daily for Not Being Able to Print Automobile-Sized Metal Objects

haha, Love it!

[ Parent | on HN ]

Re:Fakernews: Builds a Markov chain using HN post titles and... by torstenvl on Monday August 20, 2018 @06:44AM (#17798915)

What happens when you pit Markov chain fake news against Markov chain Donald Trump?

https://filiph.github.io/markov/

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Re:Fakernews: Builds a Markov chain using HN post titles and... by presscast on Monday August 20, 2018 @09:29AM (#17799701)

This seems to perform better than the OP's link. Does anybody know why that is? Are there certain forms of data for which Markov chains perform better?

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Re:Fakernews: Builds a Markov chain using HN post titles and... by torstenvl on Monday August 20, 2018 @01:08PM (#17801691)

As the sibling comment talks about, I think DJT's tweeting pattern helps. He often uses short sentences, so with Markov order 2 (every three words generated is a quote, more or less), there number of seams per sentence is lower. (By seams, I mean places where the generated text seems disjointed because the Markov chain consists of two non-semantic or semantically ambiguous tokens.)

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Re:Fakernews: Builds a Markov chain using HN post titles and... by ryneandal on Monday August 20, 2018 @11:50AM (#17800916)

I think the reason is twofold:

1. Highlighted in the conclusion of the Trump Tweet article above, the idiosyncratic voice employed by 45 makes the generated tweets very familiar to his tweeting patterns

2. The Trump Tweet chains are better optimized when it comes to probability and state management. The article goes into some detail about this in the Implementation Details section.

[ Parent | on HN ]