With the ready availability of information on the Internet, there are many situations where information can be misleading or inaccurate. Online business review services currently crowdsource reviews on businesses and at times are viewed with more frequency than those of professional critics due to ease of access and availability. Yelp has faced a heavy amount of backlash for its subjective rating process and has been criticized for unfairly penalizing smaller businesses. Each review is weighted equally regardless of a user’s 'elite' status or one’s history on Yelp. For just one business, user reviews can range widely on a scale of 1 to 5. Negative reviews can sometimes be fueled by outlying or extraordinary incidents and positive reviews are sometimes the result of marketing strategies employed by businesses to gain an artificially high rating.
In order to sort through all the misinformation and bias, this project aims to re-weight user reviews, provide more accurate ratings for businesses, and use text analysis to objectively validate these rating adjustments.
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