Mobile and web yochat system

Abstract

Social media is a phenomenon that has widely spread to people in our community due to the growth in technology and widespread of smartphone usage in our community because they ease on our ways of life through communication. Due to the advance in technology and need for new innovations in our communities, there has been vast innovation and research into creation and invention of new platforms, these have risen widely from just chatting applications but to big architectures of businesses. Among the many social platforms, there includes Facebook, WhatsApp, Instagram and Twitter, and each has its own way of interaction and functionality. There are different ways in which every person in our community is affected by the rise of social media, From our research, based on the number of chat groups like on WhatsApp, it is observed that there are most used words which can be analyzed to predict what moods people are in, based on a Machine Learning model of natural language processing. Our project, therefore, addresses the issue of information overload using text classification and sentimental analysis, a technique that is used to extract and tell how one feels about a particular interaction in a chat message or chat group, this may be classified as positive, negative or neutral.