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Match, the largest dating site in the world, pioneered the online dating category when it launched on the Web in 1995.Today, 19 years later, Match continues to revolutionize the way people meet, connect and fall in love.

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The resource would become even more useful if we could deduce complete and correct metadata from the various available information sources, such as the provided metadata, user relations, profile photos, and the text of the tweets.

In this paper, we start modestly, by attempting to derive just the gender of the authors 1 automatically, purely on the basis of the content of their tweets, using author profiling techniques.

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