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For each system, we provided the first N principal components for various N. The class separation value is a variant of Cohen s d Cohen The exception also leads to more varied classification by the different systems, yielding a wide range of scores. LP keeps its peak at 10, but now even lower than for the token n-grams Possibly, the other n-grams are just mirroring this quality of the unigrams, with the effectiveness of the mirror depending on how well unigrams are represented in the n-grams.

A group which is very active in studying gender recognition among other traits on the basis of text is that around Moshe Koppel.

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.

Then we explain how we used the three selected machine learning systems to classify the authors Section 4.

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However, we used two types of character n-grams. If you love this content, and love that it's free for everyone, please consider a donation to support our work.

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

When using all user tweets, they reached an accuracy of This means that the content of the n-grams is more important than their form.

Macros can be used to do pretty much anything you need to do on your computer with the click of a single button. One gets the impression that gender recognition is more sociological than linguistic, showing what women and men were blogging about back in A later study Goswami et al.

This may support ourhypothesis that allfeature types aredoingmore orlessthe same. We checked gender manually for all selected users, mostly on the basis 3.

For whom we already know that they are an individual person rather than, say, a husband and wife couple or a board of editors for an official Twitterfeed.

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Then, as several of our features were based on tokens, we tokenized all text samples, using our own specialized tokenizer for tweets. 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.

The only hyperparameters we varied in the grid search are the metric Numerical and Cosine distance and the weighting no weighting, information gain, gain ratio, chi-square, shared variance, and standard deviation.