Anonymous Author Similarity Identification

An increased number of social media plays a great role in the community and it has a huge positive impact on our day to day activity. However, there are some peoples associated with online anonymity by using multiple accounts and names to express their opinions on different issues. In this paper, we introduce our approach for detecting such kinds of anonymous authors by analyzing the content, the writing style and usage of the words of a user in a given text. This could be possible by looking at the written work style against a corpus of writings of known authors. We practically deploy the viability of our strategies with short messages in Twitter.