Sentiment Analysis refers to the use of natural language processing, text analysis, computational linguistics, and biometrics to systematically identify, extract, quantify, and study affective states and subjective information. Sentiment analysis is widely applied to voice of the customer materials such as reviews and survey responses, online and social media, and healthcare materials for applications that range from marketing to customer service to clinical medicine.

Generally speaking, sentiment analysis aims to determine the attitude of a speaker, writer, or other subject with respect to some topic or the overall contextual polarity or emotional reaction to a document, interaction, or event. The attitude may be a judgment or evaluation, affective state, i.e the emotional state of the author or speaker, or the intended emotional communication, i.e the emotional effect intended by the author.

Advancement in deep learning means that the ability of algorithms to analyse text has improved considerably. Creative use of advanced artificial intelligence techniques can be an effective tool for doing in-depth research. Cybersafe utilizes hi-tech softwares that utilize deep learning algorithms and artifical intelligence processes & techniques to identify accurately the negative or positive feelings of the general public regarding a particular individual, organization or topic.