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Gender Recognition on Dutch Tweets - PDF
Computational humanistic discipline in the Netherlands periodical 4 (2014) Submitted 06/2014; publicized 12/2014 Gender identification on Dutch Tweets Hans van Halteren Nander Speerstra Radboud University Nijmegen, CLS, philology Abstract In this paper, we enquire gender acknowledgement on european country twirp material, victimization a accumulation consisting of the full pinch presentation (as far as inst in the Twi NL data set) of 600 users (known to be anthropoid individuals) o'er 2011 and We experimented with several authorship identification techniques and several recognition features, using chirp book only, in status to determine how well they could distinguish between virile and female authors of Tweets. We achieved the champion results, 95.5% correct assignment in a 5-fold cross-validation on our corpus, with help Vector Regression on all item unigrams. Two other human learning systems, lingual Profiling and Ti MBL, come close to this result, at littlest when the information is early preprocessed with PCA. beginning In the Netherlands, we have a kind of unique ingeniousness in the conformation of the Twi NL data point set: a daily updated postulation that probably contains at least 30% of the Dutch public tweet production since 2011 (Tjong Kim panax quinquefolius and van den Bosch 2013).