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This uses a white list so we're trusting the open source community for what news sources are good. I guess the alternative is to use machine learning to classify fake news. But I guess it's an argument for human bias vs algorithmic error.
@delsig Hopefully it's not the "whitelist" mentioned here
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@delsig Google just funded a machine learning startup in the UK that is filtering fake news
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Problem is, only people who are conscientious about fake news are liable to use these tools. This leads to a subset of the population who, while "protected" from fake news, but doesn't see what's influencing others. Not necessarily a good thing!
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@ryanjamurphy Agreed! And mostly conscientious people won't need these tools because if they are, it means they are skeptic enough to question and do fact checks... This kind of tools are good proof-of-concept so that Facebook/Google/etc put their act together...
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What about targeting specific authors and journalists? For example, a vetted contributor at Huffington Post could conceivably push through an article that is "fake news" but the integrity of the source doesn't need to be put into question. Or conversely if a malicious individual manages to gain a publishing position with an otherwise reputable news source. Bad actors are individuals, not URLs.
For those commenting on "well, how fake is fake?" -- the readme-file clearly states that this filters scammer-sites, not biased news sources or satire sites.
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The ironic thing about this is that the mainstream media has proven to be consistently biased and dishonest in their coverage, which is why people have sought out alternative sources of news. Do not let anyone tell you that your source of news is 'fake' because it is not approved by the status quo. This is censorship plain and simple.
/ syndicate
dejavu
/ syndicate