Automatic Correction of Utterances from Social Network

The aim of this study is to construct a system for pre-processing a text, including tokenization and correction of statements from social network, in order to adapt them for further extraction of information and sentiment analysis. Correction algorithm uses dictionary methods, statistical methods and rules-based approach. The system was tested on 50 statements including different kinds of errors. The results are promising.