Abstract
With the rapid growth of internet usage, authorship authentication of online messages became challenging research topic in the last decades. In this paper, we used a team of support vector machines to authenticate 5 Twitter authors’ messages. SVM is one of the commonly used and strong classification algorithms in authorship attribution problems. SVM maps the linearly non separable input data to a higher dimensional space by a hyperplane via radial base functions. Firstly using the training data, 10 hyperplanes that separate pair wise five authors training data are built. Then the expertise of these SVMs combined to classify the testing data into five classes. 20 tweets with 16 features from each author were used for evaluation. In spite of the randomly choice of the features, one of the author accuracy around 75% is achieved.
Highlights
Authorship authentication analysis can help to display information about the writers of messages by analyzing the writing styles
One of the problems of authorship authentication analysis regarding online sources is the huge quantity of online data and a big part of candidate authors which make it more difficult
One of the main concerns in Authorship Attribution is the search for quantifiable features that are able to differentiate between authors of some text, which can be used in literary tasks of textual analysis for works edited, translated, with disputed authorship or anonymous, and with forensic aspect in view to detect plagiarism, forgery of the whole document or its constituent parts, verify ransom notes, etc
Summary
Authorship authentication analysis can help to display information about the writers of messages by analyzing the writing styles. Previous researches in the authorship authentication were showed that generally people have their unique stylistic discriminators and characteristics, just like their fingerprints or signature. In this concept, researchers are developing different analysis features and techniques and have gained remarkable results in the authorship identification research field. Author identification techniques are started to be applied to short and informal texts in last decade with this change and get very significant.
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