| Summary: | 碩士 === 淡江大學 === 資訊管理學系碩士班 === 105 === Influenced by Big Data, there are a large number of customers shared their product reviews on social media. Therefore, many researchers implement sentiment analysis technique on consumer reviews to understand the opinion tendency. However, there are few research about implement deep learning method on Chinese customer reviews. It is therefore the intent of the present study to examine the effect of sentiment analysis with deep learning method.
The study used web mining technique collected 196,651 reviews on Google Play. In addition, we use deep learning, Naïve Bayes, Support vector machine methods for sentiment analysis and compared the result.
The present study display the accuracy of the Naïve Bayes is 74.12%, the accuracy of Support vector machine is 76.46%, and the accuracy of deep learning is 94%. Our finding confirm that sentiment analysis with deep learning is outstanding.
There are three contributions in present finding. First, the present study confirm sentiment analysis with deep learning on Chinese cell phone application customers reviews may improve the accuracy of prediction. Second, the present study create a sentiment dictionary of cell phone application. Third, the study compared the result of average sampling data and non-average sampling data. We found that deep learning method with non-average sampling data reached the better performance.
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