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We selected of these so that they get a gender assignment in TwiQS, for comparison, but we also wanted to include unmarked users in case these would be different in nature.

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The best performing character n-grams normalized 5-gramswill be most closely linked to the token unigrams, with some token bigrams thrown in, as well as a smidgen of the use of morphological processes. For all feature types, we used only those features which were observed with at least 5 authors in our whole collection for skip bigrams 10 authors.

However, as any collection that is harvested automatically, its usability is reduced by a lack of reliable metadata.

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Roughly speaking, it classifies on the basis of noticeable over- and underuse of specific features. Then we outline how we evaluated the various strategies Section 3.

The best recognizable female, authoris not as focused as her male counterpart.

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We represent this quality by the class separation value that we described in Section 4. For the measurements with PCA, the number of principal components provided 50 plussers dating the classification system is learned from the development data.

All users, obviously, should be individuals, and for each the gender should be clear.

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Bigrams Two adjacent tokens. The tokenizer is able to identify hashtags and Twitter user names to the extent that these conform to the conventions used in Twitter, i.

This restriction brought the number of users down to aboutIn this paper we restrict ourselves to gender recognition, and it is also this aspect we will discuss further in this section.

The creators themselves used it for various classification tasks, including gender recognition Koppel et al. Why women of 40 and 50 are the new 'ageless generation' Polly, here with daughter Iggy, embraces an age-defying lifestyle Credit: If, in any application, unbalanced collections are expected, the effects of biases, and corrections for them, will have to be investigated.

Their highest score when using just text features was A model, called profile, is constructed for each individual class, and the system determines for each author to which degree they are similar to the class profile.

This number was treated as just another hyperparameter to be selected. With lexical N-grams, they reached an accuracy of For our experiment, we selected authors for whom we were able to determine with a high degree of certainty a that they were human individuals and b what gender they were.

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Nicole Kidman is one of the many visible plus women experiencing a career high Credit: Then, as several of our features were based on tokens, we tokenized all text samples, using our own specialized tokenizer for tweets.

We used the most frequent, as measured on our tweet collection, of which the example tweet contains the words ik, dat, heeft, op, een, voor, and het.

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These percentages 50 plussers dating presented below in Section Profiling Strategies In this section, we describe the strategies that we investigated for the gender recognition task.

The conclusion is not so much, however, that humans are also not perfect at guessing age on the basis of language use, but rather that there is a distinction between the biological and the social identity of authors, and language use is more likely to represent the social one cf.

The use of syntax or even higher level features is for now impossible as the language use on Twitter deviates too much from standard Dutch, and we have no tools to provide reliable analyses.