Popular stylometric features of Turkish author detection

I prepare a survey about author detection on Turkish for a while. I had gathered twelve studies, and then I examined them regarding preferred stylometric features and used algorithms. There are eight types of stylometric features; token-based, vocabulary richness, word frequency, word n-gram, character-based, character n-gram, part of speech and functional words.

stylometric

The numbers on the Y axis refer that how many study use this feature. The most used feature is word frequency, the second is token-based feature.

On the other hand, there are eight most preferred algorithms in the Turkish author detection studies. These algorithms are Naive Bayesian, Neural Networks, SVM, Decision Tree, Random Forest, k-NN, k-Means and other (Gaussian classifier, Histogram, similarity based etc.)

algorithmic

As shown on the graph the most preferred algorithm is Naive Bayesian, the second used algorithm is SVM, and the third one is Random Forest.

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