How Facebook Used NLP to Create Trending Topics


J. O'Dell of Venture Beat reported last week, "Facebook launched Trending, a new feature that shows you relevant-to-you topics that are spiking in popularity. It’s like Twitter’s trending topics feature, except that every person on the network sees a different list of topics based on their own personal interests, Likes, friends, location, etc. In a conversation with Chris Struhar, a software engineer on News Feed, we learned a bit about what makes Trending tick."


O'Dell continues, "First, let’s dispel the myth that Trending is in any real way linked to hashtags, which the company introduced last year. 'Hashtags and topics are two different ways of grouping and participating in conversations,' said Struhar. So don’t think Facebook won’t recognize a string as a topic without a hashtag in front of it. Rather, it’s all about NLP: natural language processing. Ain’t nothing natural about a hashtag, so Facebook instead parses strings and figures out which strings are referring to nodes — objects in the network. 'We look at the text, and we try to understand what that was about,' said Struhar. 'We’re separate from the Graph Search team, but both products want to give you more control over what you see on Facebook, to slice and dice the graph and get different pieces of information.' ”


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Image: Courtesy Facebook