Authorship Verification, Average Similarity Analysis

Authorship analysis is an important task for different text applications, for example in the field of digital forensic text analysis. Hence, we propose an authorship analysis method that compares the average similarity of a text of unknown authorship with all the text of an author. Using this idea, a text that was not written by an author, would not exceed the average of similarity with known texts and only the text of unknown authorship would be considered as written by the author, if it exceeds the average of similarity obtained between texts written by him. The experiments were realized using the data provided in PAN 2014 competition for Spanish articles for the task of authorship verification. We realize experiments using different similarity functions and 17 linguistics features. We analyze the results obtained with each pair function-features against the baseline of the competition. Additionally, we introduce a text filtering phase that delete all the sample text of an author that are more similar to the samples of other author, with the idea to reduce confusion or non-representative text, and finally we analyze new experiments to compare the results with the data obtained without