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Gender recognition has also already been applied to Tweets. (2010) examined various traits of authors from India tweeting in English, combining character N-grams and sociolinguistic features like manner of laughing, honorifics, and smiley use.
And, obviously, it is unknown to which degree the information that is present is true.
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.
However, as any collection that is harvested automatically, its usability is reduced by a lack of reliable metadata.
In this case, the Twitter profiles of the authors are available, but these consist of freeform text rather than fixed information fields.