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Since I see no reason to bore you with detailed methodologies, I made a quick and easy to follow overview of the different factors the paper considers using a random Amazon review as an example:All above outlined findings are statistically significant. Whereas previous research focussed mainly on numerical rating and length of the review, this paper looks at the textual information the review contained. This means that the practical implementations are high. For example, the paper suggests that companies may use sentiment data to analyse large amounts of OCR which are constantly produced on the Internet. The paper also showed the importance of the title: make it short and not too emotional. This is something e commerce companies can guide their customers in when writing a review. In my opinion, a large limitation of this paper is that they use the number of total votes as the number of times a review was read. I dont know about you, but I certainly dont hit the vote button every time I read a review. Hence I think using a different methodology might be better. For example you, could track customers as they move over a page, note how long they spend at the review and count the review to be read if the this time was anywhere between e. g.
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