Publication Type

Conference Proceeding Article

Version

publishedVersion

Publication Date

1-2022

Abstract

Rapid technological advances in recent years drastically transformed our world. Amidst modern technological inventions such as smart phones, smart watches and smart home devices, consumers of electronic digital devices experience greatly improved automation, productivity, and efficiency in conducting routine daily tasks, information searching, shopping as well as finding entertainment. In the last few years, the global smart speaker market has undergone significant growth. As technology continues to advance and smart speakers are equipped with innovative features, the adoption of smart speakers will increase and so will consumer expectations. This research paper presents an aspect-specific sentiment analysis of consumer reviews of the first three generations of Amazon Echo. Our text mining and aspect-specific sentiment analyses reveal that price, sound, smart home, connectivity, and comparison are outperforming aspects whereas voice, app, Q&A, companionship, and shelf life are disappointing and sunsetting aspects. Our study demonstrates a novel cross-generation visualization of directional changes in consumer sentiment using the Bollinger Bands and volume charts.

Keywords

Data Analytics, Data Mining and Machine Learning for Social Media, Amazon Echo, consumer reviews, product sequels, smart home device, text mining

Discipline

Databases and Information Systems | E-Commerce | Numerical Analysis and Scientific Computing

Research Areas

Information Systems and Management

Publication

2022 55th Hawaii International Conference on System Sciences HICSS: Virtual, January 4-7: Proceedings

First Page

2950

Last Page

2959

ISBN

9780998133157

Identifier

10.24251/HICSS.2022.364

Publisher

IEEE Computer Society

City or Country

Los Alamitos, CA

Copyright Owner and License

Authors

Additional URL

https://doi.org/10.24251/HICSS.2022.364

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