Security News > 2020 > December > A new approach to scanning social media helps combat misinformation

Rice University researchers have discovered a more efficient way for social media companies to keep misinformation from spreading online using probabilistic filters trained with artificial intelligence.

The new approach to scanning social media is outlined in a study presented by Rice computer scientist Anshumali Shrivastava and statistics graduate student Zhenwei Dai.

The social media giant recently revealed that its users added about 500 million tweets a day, and tweets typically appeared online one second after a user hit send.

"A Bloom filter allows to you check tweets very quickly, in a millionth of a second or less. If it says a tweet is clean, that it does not match anything in your database of misinformation, that's 100% guaranteed. So there is no chance of OK'ing a tweet with known misinformation. But the Bloom filter will flag harmless tweets a fraction of the time."

The typical approach is to set a tolerance threshold and send everything that falls below that threshold to the Bloom filter.

News URL

http://feedproxy.google.com/~r/HelpNetSecurity/~3/5dgM2W3dwes/