13. A system comprising: at least one computer device; a review scoring model; and a review scoring engine adapted to: receive a plurality of reviews, wherein each review was generated by an author and has an associated score; receive metadata associated with each author of a review from the plurality of reviews, wherein the metadata associated with each author includes an average score given to reviews generated by the author and an average score given to reviews generated by authors who the author has provided an indicator of trust to, wherein the average score given to the reviews generated by the author is based on scores given to reviews generated by the author, wherein each score given to a review generated by the author is given by an author or user who is not the author of the review; determine a feature vector for each review from the plurality of reviews using the received metadata associated with the author of the review and the text of each review; train the review scoring model using the feature vector for each review from the plurality of reviews and the associated scores; receive a review that is not from the plurality of reviews; receive metadata associated with the received review; determine a feature vector for the review; generate a score for the review using the feature vector for the review and the review scoring model; and apply a co-citation constraint to the generated score by skewing the generated score towards an average score given to reviews generated by authors who have provided an indicator of trust to the authors who the author has also provided an indicator of trust.
13. A system comprising: at least one computer device; a review scoring model; and a review scoring engine adapted to: receive a plurality of reviews, wherein each review was generated by an author and has an associated score; receive metadata associated with each author of a review from the plurality of reviews, wherein the metadata associated with each author includes an average score given to reviews generated by the author and an average score given to reviews generated by authors who the author has provided an indicator of trust to, wherein the average score given to the reviews generated by the author is based on scores given to reviews generated by the author, wherein each score given to a review generated by the author is given by an author or user who is not the author of the review; determine a feature vector for each review from the plurality of reviews using the received metadata associated with the author of the review and the text of each review; train the review scoring model using the feature vector for each review from the plurality of reviews and the associated scores; receive a review that is not from the plurality of reviews; receive metadata associated with the received review; determine a feature vector for the review; generate a score for the review using the feature vector for the review and the review scoring model; and apply a co-citation constraint to the generated score by skewing the generated score towards an average score given to reviews generated by authors who have provided an indicator of trust to the authors who the author has also provided an indicator of trust. 14. The system of claim 13 , further comprising applying a trust consistency constraint to the generated score, wherein applying the trust consistency constraint comprises skewing the generated score towards the average score given to reviews generated by the authors who the author has provided an indicator of trust to.