Earticle

초록

영어

Online product reviews are a vital source for companies in that they contain consumers' opinions of products. The earlier methods of opinion mining, which involve drawing semantic information from text, have been mostly applied in one dimension. This is not sufficient in itself to elicit reviewers' comprehensive views on products. In this paper, we propose a novel approach in opinion mining by projecting online consumers' reviews in a multidimensional framework to improve review interpretation of products. First of all, we set up a new framework consisting of six dimensions based on a marketing management theory. To calculate the distances of review sentences and each dimension, we embed words in reviews utilizing Google's pre-trained word2vector model. We classified each sentence of the reviews into the respective dimensions of our new framework. After the classification, we measured the sentiment degrees for each sentence. The results were plotted using a radar graph in which the axes are the dimensions of the framework. We tested the strategy on Amazon product reviews of the iPhone and Galaxy smartphone series with a total of around 21,000 sentences. The results showed that the radar graphs visually reflected several issues associated with the products. The proposed method is not for specific product categories. It can be generally applied for opinion mining on reviews of any product category.

목차

ABSTRACT
Ⅰ. Introduction
Ⅱ. Related Work
2.1. Market Sensing
2.2. Opinion Mining
2.3. Understanding Natural Language
Ⅲ. Proposed Method
3.1. Multidimensional Framework Design
3.2. Word Embedding
3.3. Sentence Classification
3.4. Sentiment Analysis
3.5. Data Visualization
Ⅳ. Experimental Setting
4.1. Data Collection
4.2. Baseline Setting
Ⅴ. Results
5.1. Words Distribution
5.2. Sentence Classification
5.3. Sentiment Data Distribution
5.4. Radar Plots
5.5. Evaluation Analysis
Ⅵ. Discussion
Ⅶ. Conclusion
Acknowledgements

저자

• Taewook Kim [ M.S. Student, Philosophy & Computer Science, Hong Kong University of Science and Technology, Hong Kong SAR ]
• Dong Sung Kim [ Postdoctoral researcher, Business Administration at the School of Business, Hanyang University, Korea ]
• Donghyun Kim [ Engineer, LG Electronics Company, Korea ]
• Jong Woo Kim [ Professor, School of Business, Hanyang University, Korea ] Corresponding author

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