On Analysis and Visualization of Twitter Data.

Provision of big data analysis in a customer-friendly applicable form, with ease and affordable cost to a wide range of customers and businesses is still a big challenge for data scientists and engineers. In this study, we focus on analysis of data and visualization of information and knowledge that eases application for customers. Present a framework for analysis. We analyze Twitter messages related to a one-year span in a specific geographical area, Okinawa Main Island. Our approach includes arranging data in a three-dimension framework of time, quality and volume. We map different elements of the data, such as number of tweets per user, time, span of time stayed in the Island, geographical location and content of messages. Based on the elements of the data within the framework, users are grouped and analyzed. A visual representation of analysis is presented.