NDLI: Consumers' Sentiment Analysis of Popular Phone Brands and Operating System Preference Using Twitter Data: A Feasibility Study

Content Provider	IEEE Xplore Digital Library
Author	Arora, D. Kin Fun Li Neville, S.W.
Copyright Year	2015
Description	Author affiliation: Dept. of Electr. & Comput. Eng., Univ. of Victoria, Victoria, BC, Canada (Arora, D.; Kin Fun Li; Neville, S.W.)
Abstract	Sentiment analysis of the text data available on the web either in the form of blogs or at social media sites such as Twitter, Facebook, and LinkedIn, offers information through which to assess people's perspective of products and services that are of interest to them. Consumers routinely scour the Internet to assess other user's reviews for a product or a service before making their own decision. Likewise, these same data can potentially provide businesses a snapshot in time of the users' response to their products/services and even the trends over time. This information gained through sentiment analysis can then be used by businesses to make decisions about improving their products and services, and gain an increased edge over their competitors. In this paper, we illustrate the potential of sentiment analysis of Twitter data to gauge users' response to popular smart phone brands and their underlying operating systems. Specifically, our objective is to investigate whether the tweets available on the web are sufficient to gain useful insight about the performance of popular smart phone brands, their battery life, screen quality, and on the perceived performance of the phones operating systems. Our results show that although the Twitter data does provide some information about users' sentiments to the popular smart phone brands and their underlying operating systems, the amount of data available for different brands varies significantly. This limitation makes the comprehensive analysis of users' response somewhat more challenging for some brands compared to others and consequently makes the comparison between brands almost impossible.
Starting Page	680
Ending Page	686
File Size	188841
Page Count	7
File Format	PDF
ISSN	1550445X
e-ISBN	9781479979059
DOI	10.1109/AINA.2015.253
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-03-24
Publisher Place	South Korea
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Smart phones Sentiment analysis Google Twitter Operating systems Batteries Business sentiment analysis business intelligence social media
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
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