Visualization for Understanding Trend Pattern of iPhone Customers

Any organization that is driven by the needs and wants of customers has to understand customer behavior from any media. Twitter is becoming one of the most popular social media in the world. Nowadays, many third-party applications of Twitter have been making customers freely to share their opinions anywhere and anytime. However, it is difficult to understand the change of customer behavior, because the tweet is posted in erratic likelihood. Therefore, visualizing the time pattern of customer emotion behavior on Twitter can play a crucial role in decision-making. Available data visualizing tools, such as D3.js, motivate us to develop and to explore time dimension of Twitter data in 2D visualization.

Autorentext

M. Nizar P. Ma'ady ha completado un programa acelerado de licenciatura y máster en Sistemas de Información en ITS (Indonesia) y NTUST (Taiwán). Actualmente cursa estudios de doctorado en el Departamento de Gestión Industrial de la Universidad Nacional de Ciencia y Tecnología de Taiwán (NTUST).