Project Abstract

Cyberbullying Detection implements our coded, machine learning algorithms, in finding a negative comment from the messages it receives by a user. The algorithm first gives the message a value and then based on our pre trained data, it decides if the comment is harsh enough to be transformed or not. If it is indeed harsh, then the system will look through our complex network of users and find how this user talks to people on average and how they talk to the end user on average. Based on this data, the system will decide if the message needs to be transformed. If so, the message is run through a series of models in order to change negative components of the sentence into positive components. The transformed sentence is then checked by our initial algorithms. It is assigned a value and if the value results in a positive sentence, the system will proceed to send the transformed positive sentence to the end user. Otherwise, the sentence will be placed through the models again. The users communicate through a developed web front face and they are connected to a central server. The users are termed as clients. If any messages are modified the receiving user will be notified along with the modified message.

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