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

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/).

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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  -