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Once you adjust for inflation, the median income in this country has stagnated for about 38 years almost two generations, even as people at the top have grown wealthier. The critique of the distribution of wealth is deduced down to just two social categories of the rich and the poor. More specifically, the pattern tells us that in discourses, people often generalize income inequality or income gap with the opposing binaries of the rich and the poor, thus creating very limiting mental schemas about the social actors involved in this issue. As a result, if this kind of language surrounding social class, such classification is how the society typically categorizes people, with regards to the amount of money and property they are entitled to. Our jobless economy has greatly influence the widening gap between the rich and the poor. NPRs classification and reinforcement of binaries, as well as description of joblessness further widens gap between the rich and the poor.

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6120. The battery voltage depends upon the chemical difference between the two plate materials and the concentration of the acid. Because the plates have become more chemically alike and the electrolyte concentration has become weaker, the voltage output gets weaker and weaker until the battery is "dead", or discharged. However, the battery can be re charged by passing an electrical current through it in the opposite direction of the discharge. The chemical reactions during a charge cycle are the reverse of those that occur during discharge. As the battery is charged the positive plates become lead dioxide again, the negative plates become pure lead again and the electrolyte returns to its proper concentration.

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Thats where the paper predicting the performance of online consumer reviews: a sentiment mining approach to big data analytics by Salehan and Kim 2015 comes in. The paper looks at the predictors of both readership and helpfulness of online consumer reviews OCR. Using different techniques the paper aims to create an approach that can be adopted by companies to develop automated systems for sorting and classifying large amounts of OCR. Sounds exciting, doesnt it?!Lets have a look at how this works. Whereas previous literature focusses at the factors that determine the perceived helpfulness of a review, this paper takes a step back. It starts by considering the factors that determine the likelihood of a consumer paying attention to a review in the first place, since without reading a review you cannot determine its helpfulness. Hence the research questions are as follows:Research Question 1: Which factors determine the likelihood of a consumer paying attention to a review?Research Question 2: Which factors determine the perceived helpfulness of a review?In order to answer the research questions, the paper looks at a sample of 2616 Amazon reviews and considers several factors they believe may impact review readership, helpfulness, or both. Readership is measured as the total number of votes helpful and not helpful, whereas helpfulness is measured as the proportion of helpful votes out of total votes. 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.