<instructions>Your goal is to analyze the following comment and estimate how highly it will be upvoted by the Hacker News community.</instructions><comment><author>euyyn</author><text>As an example, the fake news about the guy that found the warehouse full of fake ballot boxes for Clinton:&lt;p&gt;A Google Image Search of the picture in the fake article would have found the picture is much older, and isn&amp;#x27;t what the caption described.&lt;p&gt;If I&amp;#x27;m tech-savvy and skeptical, I might have done that when consuming the article, and decided on my own it was fake. Machines can do that automatically for people that aren&amp;#x27;t tech-savvy, or that don&amp;#x27;t start reading it with a skeptical mindset.</text><parent_chain><item><author>DanielBMarkham</author><text>It makes me sad to see yet another tech team go down the road of &amp;quot;machines will help us filter the truth&amp;quot;&lt;p&gt;They will not, and the reason has to do with language. Ludwig Wittgenstein tackled this 100 years ago. The best that machines will do for you is to label something as true or not &lt;i&gt;as if you had consumed the article and decided on your own&lt;/i&gt;&lt;p&gt;&lt;i&gt;That is a completely different thing from identifying fake news or truth&lt;/i&gt;&lt;p&gt;There&amp;#x27;s some value here. There are also some hard stops. You&amp;#x27;ll find them :) Best of luck, guys!</text></item></parent_chain></comment><story><title>Fake News Challenge</title><url>http://www.fakenewschallenge.org/</url></story>
<instructions>Your goal is to analyze the following comment and estimate how highly it will be upvoted by the Hacker News community.</instructions><comment><author>smsm42</author><text>I don&amp;#x27;t think it has to do with language (unless by &amp;quot;language&amp;quot; you mean what I mean, in which case sorry for duplicating). I think it has to do with that a lot of what people call &amp;quot;truth&amp;quot; is a product of their opinions, feelings, hopes, desires, etc.&lt;p&gt;There are facts of course - like such and such event happened or not, such and such statistical data is showing this number of not. But it is never served raw, it is always garnished with opinion. E.g. the fact is that Trump signed certain executive order. But you can say it&amp;#x27;s &amp;quot;Muslim ban&amp;quot; or &amp;quot;temporary restriction on admittance of nationals from terror-ridden countries&amp;quot;. Not the same.&lt;p&gt;And various &amp;quot;factchecking&amp;quot; sites are fully complicit in this and inject opinion as often as not - to the point exactly the same thing said by two different people can be deemed &amp;quot;mostly true&amp;quot; or &amp;quot;mostly false&amp;quot;, moreover, exactly the same thing said by the same person can be &amp;quot;mostly true&amp;quot; and &amp;quot;false&amp;quot;.&lt;p&gt;You can&amp;#x27;t hope to have robots make sense of it if we can&amp;#x27;t. You can, of course, build a neural network and train it, but it would just put &amp;quot;robot approved&amp;quot; stamp on biases of whoever trained it.</text><parent_chain><item><author>DanielBMarkham</author><text>It makes me sad to see yet another tech team go down the road of &amp;quot;machines will help us filter the truth&amp;quot;&lt;p&gt;They will not, and the reason has to do with language. Ludwig Wittgenstein tackled this 100 years ago. The best that machines will do for you is to label something as true or not &lt;i&gt;as if you had consumed the article and decided on your own&lt;/i&gt;&lt;p&gt;&lt;i&gt;That is a completely different thing from identifying fake news or truth&lt;/i&gt;&lt;p&gt;There&amp;#x27;s some value here. There are also some hard stops. You&amp;#x27;ll find them :) Best of luck, guys!</text></item></parent_chain></comment><story><title>Fake News Challenge</title><url>http://www.fakenewschallenge.org/</url></story>