Reuters uses an algorithm to spot breaking news on Twitter
Ricardo Bilton of the Nieman Lab reports that Reuters has created an algorithm to help it spot and verify breaking news on Twitter.
Bilton writes, “Once the tool identifies what it thinks are emerging stories, it clusters relevant tweets into events, generating information, and metadata about what that story might be about. Tweets that mention ‘explosions’ and ‘bombs,’ for example, would be clustered into a single story about a potential terrorist attack.
“But detection is only the first, and probably easiest, problem to solve. Another challenge was figuring out how to identify which events are actually interesting, newsworthy, and not spam. Added to that is the problem of filtering out assertions of opinions (‘I think it’s terrible that this event happened’) from assertions of facts (‘This event happened’) and automating the processing of verifying whether reports are actually true.
“The verification challenge was the most interesting and most valuable problem to solve, Chua said. Pulling from academic research on the verification of social media reports, Reuters designed its algorithm to assign verification scores to tweets based on 40 factors, including whether the report is from a verified account, how many people follow those who reported the news, whether the tweets contain links and images, and, in some cases, the structure of the tweets themselves. ‘Amazingly enough, a tweet that is entirely in capital letters is less likely to be true,’ Chua said.
“The factors, when combined, give each story cluster a score. If those stories meet a set verification threshold, Reuters has enough confidence to tweet out its own breaking news alert reporting the event, and reporters will then report on the story themselves. That score will also change over time, as more reports come in and increase or decrease the verification ranking.”
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