Mining Chat Conversations for Sex Identification

Abstract

Chat mediums are becoming an important part of human life in societies and provide quite useful information about people such as their current interests, habits, social behaviors and tendencies. In this study, we have presented an identification system to identify the sex of a person in a Turkish chat medium. Here, the sex identification is taken as a base study in the information mining in chat mediums. This system acquires data from a chat medium, and then automatically detects the chatter’s sex from the information exchanged between chatters and compares them with the known identities of the chatters. To do this task, a simple discrimination function is used to determine the sex of the chatters. A semantic analysis method is also proposed to enhance the performance of the system. The system with the semantic analyzer has achieved accuracy over 90% in the sex identification in the real chat medium.

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