In this information age, Internet is growing exponentially with large amount of information through social media networks like Facebook, Blogs, Twitter, LinkedIn, etc. Most of the text we have seen in Internet are anonymous in nature. Analysis of such kind of text became crucial nowadays. Author Profiling is a technique which is used to analyse the anonymous text in Internet for finding out the characteristics of author like age, gender, country, native language, educational background etc. Style of writing of each author is utilized for the analysis of different characteristics of author’s profile. Researchers experimented with different types of features to improve the accuracy of prediction. The final accuracy of prediction depends on the feature which is extracted and on the machine learning algorithm used for prediction. The various application domains of author profiling are forensics, security, marketing and education. In this paper the various author profiling approaches and techniques are explained and their performances are analysed.

Author Profiling, Stylometric Features, Machine Learning Algorithms, Features, Accuracy

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