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Automated Data Collection with R: A Practical Guide to Web Scraping and Text Mining by Dominic Nyhuis, Peter Meissner, Christian Rubba, Simon Munzert

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17 Analyzing sentiments of product reviews

17.1 Introduction

In the previous chapter, we have assembled several pieces of structured information on a collection of mobile phones from the Amazon website. We have studied how structural features of the phones, most importantly the cost of the phones, are related to consumer ratings. There is one important source of information on the phones we have disregarded so far—the textual consumer ratings. In this chapter, we investigate whether we can make use of the product reviews to estimate the consumer ratings. This might seem a fairly academic exercise, as we have access to more structured information on consumer ratings in the form of stars. Nevertheless, there are numerous circumstances where such structured information on consumer reviews is not available. If we can successfully recover consumer ratings from the mere texts, we have a powerful tool at our disposal to collect consumer sentiment in other applications.

In fact, while structured consumer ratings provide extremely useful feedback for producers, the information in textual reviews can be a lot more detailed. Consider the case of a product review for a mobile phone like we investigate in the present application. Besides reviewing the product itself, consumers make more detailed arguments on the specific product parts that they like or dislike and where they find fault with them. Researchers have made some effort to collect this more specific review (Meng 2012; Mukherjee ...

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