Sentiment Analysis on Big Data Using Machine Learning Algorithms

Abstract

Data Analysis which means the data which is obtained that is converted into useful information. Data analysis begins with data through its raw state and turns it into a format that is more readable in the form of graphs, records, plots, etc. allowing it the state and meaning to be understood. After the data is obtained, it reaches the stage of data planning. The level at which raw data is cleaned up and prepared for the next stage of data processing is data planning, also referred to as "pre-processing". Raw data were diligently reviewed for any faults during planning. This move are meant to remove bad data. Therefore the clean data is entered into it and converted into a language it can comprehend. The first step in which raw data starts to take the form of functional information is data entry. The data inserted into the machine in the previous stage is actually analyses for analysis during this step. Machine learning algorithms are used to process the process, but the process itself can differ slightly depending on the data source being processed. The step of output / interpretation is the stage at which data will ultimately be used by non-data researchers. It's accessible and translated.