Toxic Sentiment Identification Using R Programming
Text messaging has become a universal staple. WhatsApp is regularly becoming a news delivery channel as users rely on its broadcast messages to share both local and international news. Today we are not utilizing and operating it, but it is operating us which can confirm to be very unsafe for us. Most of the fake news spread rapidly by WhatsApp. So, there is requirement to examine WhatsApp chat by user’s sentiment or opinion. WhatsApp is such an application which is used widely for transferring media, text, files as well as audio calling. WhatsApp is progressively becoming a turning point in numerous sectors like healthcare, education and business. So, there is requirement to inspect WhatsApp chat by user’s sentiment or opinion. The advent of the internet had played a huge role in expanding the usage of text messaging to instant messaging on mobile devices. WhatsApp chat sentiment analysis to increase improved insights regarding their employees and strive to stay away from unanticipated conflicts due to various redundancies and insufficiency of business processes. Sentiment analysis is most popular branches of textual analytics which with the aid of information and natural language processing observe and categorize the unorganized written data into different sentiments. It is as well as acknowledged as opinion mining. Most of the false news increase rapidly by WhatsApp. Therefore, there is call for to observe and examine WhatsApp chat to find user’s sentiment or opinion. Firstly, chat from WhatsApp is selected and exported to a system which is an easy task and can be done either by phone or WhatsApp for the computer system. Following this, the processes are fairly simple and have been explained with all the coding details needed to analyze the texts. In this project, chat of WhatsApp has been used as database by using R, sentiments and emotions are being analyzed.