Abstract:

With the development of the internet, digital texts are proliferating. Protection of a copyright has become increasingly important in recent years. To solve the copyright problem, one way is to profile an author's writing style. By comparing writing styles, we could tell whether a text has been written by a certain author. Most of the current researches in author profiling focused on examining linguistic attributes or finding new attributes. However, the appropriate profiling of an author is still a challenging task. This paper aims to build a model to fingerprint an author, and took texts of an author of a certain domain as input and produced a profile of the author as output. Using this fingerprint engine we can tell with a certain probability whether an input text has been written by an author among a list of possible authors. This paper focused on author profiling of English texts. Writing styles were measured using linguistic attributes and linguistic measurements. Statistical methods, such as standard deviation analysis and principal components analysis, were used to evaluate the linguistic measurement's efficiency.

Key words: author profiling; text analysis; natural language processing; data mining; artificial intelligence