Author Profiling, instance-based Similarity Classification

In digital documents analysis for forensic applications, when anonymous documents are presented and it is not possible with the available tools to determine the true author of the document, there are of vital importance methods that identify the characteristics of the Author Profile (Gender, Age, Personality, etc.). We propose to use a simple method of classification based on the similarity between objects, considering different features for documents representation: (a document corresponds to a set of tweets of a user), the terms used in the tweets, as well as characteristics of opinion and subjectivity presented in them. Our goal will be to classify, based on the content of the tweets, the Gender and language variety of an author from an unknown set of tweets corresponding to him. In the experiments we observed good results in Gender classification, but low values in language variety classification. We processed only the English dataset.