<story><title>Meta in Myanmar, Part III. The Inside View</title><url>https://erinkissane.com/meta-in-myanmar-part-iii-the-inside-view</url></story><parent_chain><item><author>theptip</author><text>&amp;gt; the most generous number from the disclosed memos has Meta removing 5% of hate speech on Facebook. That would mean that for every 2,000 hateful posts or comments, Meta removes about 100–95 automatically and 5 via user reports.&lt;p&gt;Its really hard to contextualize these numbers. What are the comparable rates for other media?&lt;p&gt;What % of hate speech on Mastodon is taken down? Twitter? YouTube? Discord? Comparing with old-school mob formation technology, what about leaflets handed out? Political rallies?&lt;p&gt;Meta is an obvious target because they have such a high % of total online speech, and by virtue of this make a potentially impactful single intervention point to make things better. And these articles do make it seem they have room at the margin to improve. But imagine a word with multiple social networks per country - do we think they would be better or worse at policing this stuff (and crucially, the places where it matters are the developing less-regulated countries, often with governments that are at least disinterested in preventing the ethnic conflicts, if not actively promoting them)? I can see hand-wavey arguments in both directions but what I really want is data analyzing the question.</text></item></parent_chain><comment><author>intended</author><text>The term is Prevalence. I have been looking for years, and have essentially shifted careers to find it. I didnt even have a name for it until recently. 
There is also no way to get the data you are looking for. As someone described it - this is akin to asking how much crime happens every day.&lt;p&gt;You could get an approximation - For resourced languages though.&lt;p&gt;Meta launched Hindi classifiers in 2021 and Bengali in 2022, covering 0.6bn and 0.24bn people, respectively. I know how poor the lexicons I have seen in the wild are, and how hard it is to stay ahead of terminology.&lt;p&gt;Meta is probably doing more to stay ahead than others. However the ARPU for a user in the US vs India is stark.&lt;p&gt;Platforms aren’t going to release the necessary data for even a rough approximation. Reddit was a potential data source to learn from, but now we have the API rules, so that is also closed off. Lucky us.&lt;p&gt;Not to mention how supremely unprepared society is to actually understand or discuss the data without making it worse.&lt;p&gt;Meta has more resources and frankly they regained my trust years ago. However,  business is business. Twitter and Reddit have shown that in this current cycle, there are are no consequences for neglecting Trust and Safety, as shown by other companies. T&amp;amp;S teams have been reduced globally. T&amp;amp;S teams are being targeted and vilified.&lt;p&gt;Next year, there are ~50 elections happening, including the USA and India. The network suits certain narratives - the more insular, fear driven ones. Trust and Safety teams are themselves being exposed.&lt;p&gt;Its already looking like a perfect storm.</text></comment>
<story><title>Meta in Myanmar, Part III. The Inside View</title><url>https://erinkissane.com/meta-in-myanmar-part-iii-the-inside-view</url></story><parent_chain><item><author>theptip</author><text>&amp;gt; the most generous number from the disclosed memos has Meta removing 5% of hate speech on Facebook. That would mean that for every 2,000 hateful posts or comments, Meta removes about 100–95 automatically and 5 via user reports.&lt;p&gt;Its really hard to contextualize these numbers. What are the comparable rates for other media?&lt;p&gt;What % of hate speech on Mastodon is taken down? Twitter? YouTube? Discord? Comparing with old-school mob formation technology, what about leaflets handed out? Political rallies?&lt;p&gt;Meta is an obvious target because they have such a high % of total online speech, and by virtue of this make a potentially impactful single intervention point to make things better. And these articles do make it seem they have room at the margin to improve. But imagine a word with multiple social networks per country - do we think they would be better or worse at policing this stuff (and crucially, the places where it matters are the developing less-regulated countries, often with governments that are at least disinterested in preventing the ethnic conflicts, if not actively promoting them)? I can see hand-wavey arguments in both directions but what I really want is data analyzing the question.</text></item></parent_chain><comment><author>arczyx</author><text>Rather than the 5% number (which may be the best they can do with current start of art), what feels more damning to me is that they found a method that can reduce misinformation (by way more than 5%), and then decided to &lt;i&gt;rollback&lt;/i&gt; it.&lt;p&gt;&amp;gt; And this method works. In Myanmar, “reshare depth demotion” reduced “viral inflammatory prevalence” by 25% and cut “photo misinformation” almost in half.&lt;p&gt;&amp;gt; In a reasonable world, I think Meta would have decided to broaden use of this method and work on refining it to make it even more effective. What they did, though, was decide to roll it back within Myanmar as soon as the upcoming elections were over.</text></comment>