The prevalence of social media and online user-generated content has transformed the way investors are beginning to evaluate and predict company stock performance. In today’s world, product reviews become an instant gauge of consumer pulse, and this feedback is a leading indicator of the way the markets will respond to the underlying product manufacturer’s stock. Researchers from the academic journal Market Science have determined that negative chatter about a product immediately after the release date can account for significant decreases in stock price – well before sales figures and unit volume numbers are released. In the case of positive reviews, the subsequent increase in stock performance is not as drastic, but the relationship is still meaningful.
One complication of this finding is that product reviews are extremely scattered across the Internet. There are thousands of e-commerce sites, individual merchants, and original manufacturers that collect reviews, and none of the ratings or methodologies are standardized. Fortunately, several product review platforms have emerged with the aim of aggregating and standardizing reviews across the Internet. Using big data analytics and classification methods, these platforms coalesce all of the product review information for a particular item into one digestible format that allows consumers to make an informed purchase decision. For example, this product review on the best paper shredders is a comprehensive guide to the plethora of shredders that are reviewed across the Internet. The platform uses data mining techniques to extrapolate language across all the reviews of paper shredders on the Internet, combing through phrases like “this shredder frequently gets jammed when processing multiple pages,” “the shredder’s blades are extremely strong and durable,” and “the motor overheats after reaching its feed capacity,” in order to algorithmically evaluate the highest quality model on the market. As a result, these review sites are able to provide an easily digestible summary of the top models for each category. While originally designed for consumers to make more informed purchase decisions, investors and speculators are now also finding them useful as they analyze company stock market performance and make trading decisions.
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