TY - JOUR
T1 - Twitter Sentiment to Analyze Net Brand Reputation of Mobile Phone Providers
AU - Vidya, Nur Azizah
AU - Fanany, Mohamad Ivan
AU - Budi, Indra
N1 - Funding Information:
This work is supported by Higher Education Center of Excellence Research Grant funded by Indonesia Ministry of Research, Technology and Higher Education. Contract No. 0475/UN2.R12/HKP.05.00/2015.
Publisher Copyright:
© 2015 The Authors.
PY - 2015
Y1 - 2015
N2 - We may see competition among mobile providers to acquire new customers through campaign and advertisement war, especially on social media. The problem arises on how to measure the brand reputation of these providers based on people response on their services quality. This paper addresses this issue by measuring brand reputation based on customer satisfaction through customer's sentiment analysis from Twitter data. Sample model is built and extracted from 10.000 raw Twitter messages data from January to March 2015 of top three mobile providers in Indonesia. We compared several features extractions, algorithms, and the classification schemes. After data cleaning and data balancing, the sentiments are classified and compared using three different algorithms: Naïve Bayes, Support Vector Machine, and Decision Tree classifier method. We measure customer satisfaction on five products: 3G, 4G, Short Messaging, Voice and Internet services. This paper also discusses some correlated business insights in a telecommunication services industry. Based on the overall comparison of these five products, the NBR scores for PT XL Axiata Tbk, PT Telkomsel Tbk, and PT Indosat Tbk are 32.3%, 19.0%, and 10.9% respectively.
AB - We may see competition among mobile providers to acquire new customers through campaign and advertisement war, especially on social media. The problem arises on how to measure the brand reputation of these providers based on people response on their services quality. This paper addresses this issue by measuring brand reputation based on customer satisfaction through customer's sentiment analysis from Twitter data. Sample model is built and extracted from 10.000 raw Twitter messages data from January to March 2015 of top three mobile providers in Indonesia. We compared several features extractions, algorithms, and the classification schemes. After data cleaning and data balancing, the sentiments are classified and compared using three different algorithms: Naïve Bayes, Support Vector Machine, and Decision Tree classifier method. We measure customer satisfaction on five products: 3G, 4G, Short Messaging, Voice and Internet services. This paper also discusses some correlated business insights in a telecommunication services industry. Based on the overall comparison of these five products, the NBR scores for PT XL Axiata Tbk, PT Telkomsel Tbk, and PT Indosat Tbk are 32.3%, 19.0%, and 10.9% respectively.
KW - Indonesia
KW - Naïve Bayes
KW - brand reputation
KW - decision tree
KW - sentiment analysis
KW - support vector machine
KW - twitter
UR - http://www.scopus.com/inward/record.url?scp=84964034621&partnerID=8YFLogxK
U2 - 10.1016/j.procs.2015.12.159
DO - 10.1016/j.procs.2015.12.159
M3 - Conference article
AN - SCOPUS:84964034621
SN - 1877-0509
VL - 72
SP - 519
EP - 526
JO - Procedia Computer Science
JF - Procedia Computer Science
T2 - 3rd Information Systems International Conference, 2015
Y2 - 16 April 2015 through 18 April 2015
ER -