Abstract: A method, system, and product for filtering out unwanted social media content in real-time. The system comprises multiple sets of machine learning classifiers to filter out the unwanted content on any media including but not limited to text, images, audio, and video. Classifiers are trained with labeled data. After being trained, the models screen the incoming real-time data either on a server or a mobile device. A user application is run that results in only approved content to be displayed on the main screen of the user application device. The unwanted data are still available if the user desires to access them. The classifiers are trained with labeled data; and with input parameters in addition to the labeled data. On the device, customized models are trained with the individual user data and Transfers Learning models. When unwanted content is detected, a report is sent to an entity that might help support the receiver.

Abstract: A method, system, and product for filtering out unwanted social media content in real-time. The system comprises multiple sets of machine learning classifiers to filter out the unwanted content on any media including but not limited to text, images, audio, and video. Classifiers are trained with labeled data. After being trained, the models screen the incoming real-time data either on a server or a mobile device. A user application is run that results in only approved content to be displayed on the main screen of the user application device. The unwanted data are still available if the user desires to access them. The classifiers are trained with labeled data; and with input parameters in addition to the labeled data. On the device, customized models are trained with the individual user data and Transfers Learning models. When unwanted content is detected, a report is sent to an entity that might help support the receiver.