Proceedings of the 2016 International Conference on Economy, Management and Education Technology

Application for Product Features Extraction and Sentiment Analysis from Online User Reviews

Authors
Li Xue, Lei Sun
Corresponding Author
Li Xue
Available Online May 2016.
DOI
10.2991/icemet-16.2016.415How to use a DOI?
Keywords
User reviews; product features; data mining; sentiment analysis.
Abstract

Based on the existing research results, the product reviews mining technology is applied in the analysis of competitive advantages of mobile phones in this paper. Taking iPhone SE and Galaxy S7 edge as the research objects, first, extract product features from the online reviews by FP-growth algorithm and rank them according to users attention. Subsequently, calculate the sentiment polarity of words. This paper ends with the advantages and disadvantages analysis of the competitive products, as well as the direction to improve. Some enlightenment from this paper to domestic consumer electronics business is expected.

Copyright
© 2016, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Download article (PDF)

Volume Title
Proceedings of the 2016 International Conference on Economy, Management and Education Technology
Series
Advances in Social Science, Education and Humanities Research
Publication Date
May 2016
ISBN
10.2991/icemet-16.2016.415
ISSN
2352-5398
DOI
10.2991/icemet-16.2016.415How to use a DOI?
Copyright
© 2016, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Li Xue
AU  - Lei Sun
PY  - 2016/05
DA  - 2016/05
TI  - Application for Product Features Extraction and Sentiment Analysis from Online User Reviews
BT  - Proceedings of the 2016 International Conference on Economy, Management and Education Technology
PB  - Atlantis Press
SP  - 1805
EP  - 1810
SN  - 2352-5398
UR  - https://doi.org/10.2991/icemet-16.2016.415
DO  - 10.2991/icemet-16.2016.415
ID  - Xue2016/05
ER  -