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The age component of the system is described in (Nguyen et al. The authors apply logistic and linear regression on counts of token unigrams occurring at least 10 times in their corpus.
The paper does not describe the gender component, but the first author has informed us that the accuracy of the gender recognition on the basis of 200 tweets is about 87% (Nguyen, personal communication). (2014) did a crowdsourcing experiment, in which they asked human participants to guess the gender and age on the basis of 20 to 40 tweets. on this, we will still take the biological gender as the gold standard in this paper, as our eventual goal is creating metadata for the Twi NL collection. Experimental Data and Evaluation In this section, we first describe the corpus that we used in our experiments (Section 3.1).
For gender, the system checks the profile for about 150 common male and 150 common female first names, as well as for gender related words, such as father, mother, wife and husband.
If no cue is found in a user s profile, no gender is assigned.
172 For Tweets in Dutch, we first look at the official user interface for the Twi NL data set, Among other things, it shows gender and age statistics for the users producing the tweets found for user specified searches.