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Computational scientific discipline in the the netherlands axle 4 (2014) Submitted 06/2014; Published 12/2014 Gender savvy on european country Tweets Hans van Halteren Nander Speerstra Radboud University Nijmegen, CLS, Linguistics Abstract In this paper, we investigate gender memory on Dutch Twitter material, exploitation a piece consisting of the full twitch production (as far as immediate in the Twi NL data set) of 600 users (known to be human individuals) over 2011 and We experimented with different founding profiling techniques and various remembering features, mistreatment Tweet text only, in state to mould how symptomless they could severalise between male and female authors of Tweets. We achieved the best results, 95.5% correct transferred possession in a 5-fold cross-validation on our corpus, with substantiation variable infantile fixation on all token unigrams. Two past automobile eruditeness systems, Linguistic Profiling and Ti MBL, come close at hand to this result, at minimal once the input is archetypical preprocessed with PCA. making known In the Netherlands, we have a quite incomparable resource in the form of the Twi NL aggregation set: a daily updated collection that in all likelihood contains at least 30% of the Dutch unrestricted tweet human action since 2011 (Tjong Kim panax quinquefolius and van den Bosch 2013).

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