The 'Brand Safety' and 'Suitability' industries have financially crushed the news business by keeping ads away from articles that its 'sentiment analysis' algorithms think will make people sad or upset.

The ‘Brand Safety’ and ‘Suitability’ industries have financially crushed the news business by keeping ads away from articles that its ‘sentiment analysis’ algorithms think will make people sad or upset.

  • Cockmaster6000@sh.itjust.works
    709·
    1 year ago

    This is pure cope from the talentless cretins who ran jezebel (into the ground, all by themselves).

    They had not produced any meaningful journalism for several years. But sure, their downfall was caused by the secret conspiratorial algorithm that took ad money away.

    • stopthatgirl7@kbin.socialOP
      1626·
      1 year ago

      So Cory Doctorow - y’know, the guy who created the term “enshittification,” is also just “coping,” eh?

      There’s a bigger issue here than just a site you don’t think has value shutting down.

      • Cockmaster6000@sh.itjust.works
        266·
        1 year ago

        So Cory Doctorow - y’know, the guy who created the term “enshittification,” is also just “coping,” eh?

        Yes. Half that post is whining about conservatives and the other half is just repeating the content from the 404media article, without adding any additional value.

        There’s a bigger issue here than just a site you don’t think has value shutting down.

        When your business model revolves around ad money, you toe the line or die. It has always been this way.

        Jezebel died because it had no readers, not because its content was so upsetting to The Man that they were demonetized. We’re just hearing the pearl-clutching righteous indignation of people too proud to accept that they lost because they suck.

  • poo@lemmy.worldEnglish
    217·
    1 year ago

    Jezebel was awful and deserved to be shut down a long time ago.

    • psmgx@lemmy.world
      2·
      1 year ago

      Sentiment analysis is basic data mining.

      Get access to an API and scan the tweets / posts / whatever and look for key words. Hate, dumb, wtf, love, awesome, etc. You can get 60-80% accuracy just counting the number of words that express a sentiment. Literally that simple, just count positive and negative words/phrases. Across a large dataset you can get a decent idea what people think, and there are easy ways to dig deeper.

      And that was the half-assed quick approach, folks who know Markov chains and LLMs could do far, far deeper analysis.