Detection of Human Trafficking on Social Media Platforms using Natural Language Processing

Abstract

Human trafficking is one of the widespread challenges that exist all over the world. Due to improvement in technology the traffickers’ growth rate is also advanced. In the present era individuals are doing this crime using social networks .Since criminal justice agencies are very less it is very important to find the offense messages related to this crime and take necessary actions in order to avoid human exploitation especially the young people and ensuring them safety. By using Natural language processing we will be able to find out the victim who is harmed as a result of this crime .Firstly the post associated with hash tags especially twitter are mined and we find out whether the messages are mistrustful or no if it is then we get the web link from that and we find Images on that link and find out the victim who has been targeted. The victim can be anyone irrespective of their age, identity etc. Victims may need support and assistance so we find out the one who is responsible for this trafficking. The person’s age and identity can be determined whether they are less than 14 years of age or no and by using Support Vector Machines and Convolutional Neural Network we can rescue the victims from human trafficking and also take necessary actions to stop these crimes.