December 1, 2015

Netflix Employs Human “Taggers” to Add Metadata to Suggestion Database


Every week, [Jordan] Canning receives a list of movies and TV shows. Usually there are about five, ranging from Quebecois preschool shows to crazy violent Sci-Fi flicks.

She watches each with a spreadsheet open on her laptop and notes every detail imaginable in the film. Does it end tragically or have a happy one? Was there a high squirm factor? What about the use of curse words?

“It covers everything from big picture stuff like storyline, scene and tone, to details of whether there is a lot of smoking in the movie,” Canning says.

Each Netflix entry in the massive Netflix library is tagged with north of 100 data points. Some are simple, like the gender and jobs of the main characters. Others are ratings, like how violent is the title on a scale of one to five?

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Hat Tip: Hacking Netflix

Gary Price About Gary Price

Gary Price ( is a librarian, writer, consultant, and frequent conference speaker based in the Washington D.C. metro area. Before launching INFOdocket, Price and Shirl Kennedy were the founders and senior editors at ResourceShelf and DocuTicker for 10 years. From 2006-2009 he was Director of Online Information Services at, and is currently a contributing editor at Search Engine Land.

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