Posted: February 11th, 2022
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At 12:01 PM on January 20th, Donald Trump became a “former president”, some say, the worst one ever. I tend to agree.
On January 8, Twitter took the extraordinary act of indefinitely banning Trump from its platform for “risk of further incitement of violence”. In a statement that appeared on their blog () they explained the ban decision further.
Interestingly, on January 16, just about a week after the ban, Washington Post reported that the research firm Zignal Labs had found that online misinformation about election fraud had plunged 73 percent after Twitter banned Trump. Wow, Oh, what a difference a week makes.
Misinformation is a serious problem in social media. Twitter wants to reduce misinformation on its platform. It is bad for business, so they claim. The decision by Twitter to ban Trump was not an easy one. But it resulted in a big plunge in production and spread of misinformation. Twitter decision to ban Trump was made by a committee of senior staff. Twitter has over 330 million user. Each one of these 330 million could become a purveyor of misinformation. Despite given the stated goal of Twitter wanting to reduce misinformation on its platform, it is hard to imagine that Twitter would convene such a committee every time it needs to decide whether to ban any of its 330 million users. There must be a better way….
Now, as a cognitive computing expert, please give them some advice and comment on whether a cognitive computing based application (e.g., NLP system) could be help them facilitate and streamline the ban/not ban decision. If so, what would be the characteristics of such a system? What are the major issues that need to be explored before such a system is implemented?
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