Abstract—Competition between telephone providers to
attract new customers can be seen through advertisment war on
TVs, posters and radios nearly every moment. Question is arise
on how do we measure the quality of these providers in order
choose the best one for oneself.
This paper is written to solve the question by measuring
customers satisfaction by using text mining. Sample model is
extracted from social media Twitter and the sentiment polarity
is measured using Naïve Bayes classifier method. The model
shows a promising result on defining the popularity based on
customer's satisfaction and therefore defining the best provider
to be used
Index Terms—Naïve bayesian, sentiment analysis, telephone provider, text mining.
Calvin and Johan Setiawan are with the Information System Department, Faculty of Information and Communication Technology, Multimedia Nusantara University, Scientia Boulevard Street, Gading Serpong, Tangerang, Banten-15811, Indonesia (e-mail: firstname.lastname@example.org; email@example.com).
Cite:Calvin and Johan Setiawan, "Using Text Mining to Analyze Mobile Phone Provider Service Quality (Case Study: Social Media Twitter)," International Journal of Machine Learning and Computing vol.4, no. 1, pp. 106-109, 2014.