Özet:

Abstract This paper aims to provide an analysis of anaphoric relations in tweets in Turkish language. The analysis offered rests on the results of a sequence of experiments conducted using a group of machine learning algorithms. The algorithms used in this study are J48, Voted Perceptron, SVM (support vector machine), Naive Bayes and k-nearest neighbours. These classifiers were experimented by parametric variations are scrutinized to elaborate on the problem of matching a model conveniently to the task available already. Another important contribution of the paper is the comparison offered between two genres of texts, namely tweets versus child stories. Our experimental results are compared with those of the previous work and, thereby, a comparison is offered between the anaphoric structure of tweets and that of child stories in Turkish.

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