Machine Learning Could Help Filter Social Media's ‘Noise'
Panelists from WorldQuant, Thomson Reuters, OneMarketData and the Federal Home Loan Bank of Chicago discussed the challenges of tapping into the power of social media.
![Social Media Social Media](/sites/default/files/styles/landscape_750_463/public/import/IMG/648/268648/social-media-mobile-icons.jpg.webp?h=b2acb991&itok=7eq6DGNC)
When it comes to social media, it's always going to be a case of good and bad. Sites like Twitter and Facebook both connect and divide. But they also serve as potentially valuable sources of information.
Many trading firms have tried to tap into the power of public sentiment. It stands to reason that as firms can more affordably and easily take in more data, it will be more tempting to target social media outlets. And that's largely what's happened, but many have been disillusioned by social
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