Published Paper Details:

The task of analyzing an interested text to find demographic characteristics such as gender, age, country and nativity language of an unknown author based on the writing style of the text called Author Profiling. The writing style differences are very important in Author Profiling research. Different researchers proposed several stylistic features to differentiate the writing style of the authors. In this work, the experimentation carried out with content based features like most frequent terms in the corpus to predict the nativity language of the authors. A Profile specific Document Weighted approach is used with most frequent terms as features. In this approach, the document weights are used to represent the document vectors. Various classification algorithms were used to generate the classification model and to predict the nativity language of the authors. The achieved results were good when compared with exiting techniques for nativity language prediction in Author Profiling research area.