Author Description

Online communities accumulated a huge database of accounts, which contain many data about the person. The audience of web services is a large number of people regardless of age, gender, occupation, education, ethnicity, social status etc. Nowadays, the necessity of verifying online community users' personal data is the topical issue. The variance styles of user content, posts and account data investigated using approaches of gender linguistics, sociolinguistics and internet communications. The comprehensive analysis of language features in online communication lies in study of online users' information track, which gives an opportunity to ascertain similarities and differences in online identity and language use of certain online users groups. In this monograph presented the new approaches to analysis of the online communication. To solve this tasks the mathematical linguistics methods used to define Manhattan and Euclidean distances, to analyze online content – software developed by means of Borland Delphi and Python. Computer-linguistic analysis essential helps to administrators and moderators to monitor and validate personal data provided by online community users.