SENTIMENTAL ANALYSIS OF WHATSAPP DATA USING DATA ANALYTICS TECHNIQUES

Abstract

Data, the one, that made a trend and evolution from good old techniques to modern trendy techniques. Based on the source the data is extracted, its form differs that is in recent decades data are scalable, skeptical and diverse compared to old structured data that are derived from specific known sources.The next criterion for the technological evolution is, the storage
space that is needed for data. Structured data storage lies in the database whereas for the unstructured and semi-structured ones the storage trend tips to cloud. The vital thing in addition to storage is data handling and analysis, both process when involved in trendy data results in a complexity in terms of containment, processing and visualization of data. To overcome these complexities on trendy unstructured data there emerged a concept called Big
Data Analytics. It uses numerous tools and techniques that resolved the problem from data storage to visualization. One such technique is Analytical sandbox, the most central container that stores and handles data in a very appropriate manner. In addition, Big data tools provide a variety of analytical and visualization techniques that produces efficient graphical view of modern data. This paper centered on sentimental analysis of WhatsApp group data in which text mining was incorporated to the chat file and the resulted chat text file is further processed with analytical tools that analyze the chat contents and produces an graphical visualization of the sentiments shared in the group. Its outcome view lies in high echelon of positive opinions compared to other emotions such as anger, fear, disgust, anticipation, joy, sadness, surprise, trust and negative.