Models of natural languages and language characteristics are widely used in many computer science applications such as data security, language identification, spell checking, data compression, authorship attribution and speech recognition. In the scope of this study, a large scale corpus is created and used to discover language characteristics of Turkish. Word and letter based analyses are made on this corpus to build a base for several NLP studies. In the author identification part, we used two different methods based on word n- grams to identify author of an anonymous text. For 16 authors, training and test set articles are collected, and mentioned two methods are applied on these article sets. Finally, obtained results from two methods are compared with each other and most successful method is determined. This study can help professionals working on author identification, corpus linguistics, n-gram analysis, cryptanalysis, and speech recognition.