In our prior work ( Xiong and Litman , 2011 ) , we examined whether techniques used for predicting the helpfulness of product reviews ( Kim et al. , 2006 ) could be tailored to our peer-review domain , where the definition of helpfulness is largely influenced by the educational context of peer review .
automatically predicting peerreview helpfulness
Wenting Xiong Diane Litman
Such an intelligent component could enable peer-review systems to 1 ) control the quality of peer reviews that are sent back to authors , so authors can focus on the helpful ones ; and 2 ) provide feedback to reviewers with respect to their reviewing performance , so students can learn to write better reviews . In our prior work ( Xiong and Litman , 2011 ) , we examined whether techniques used for predicting the helpfulness of product reviews ( Kim et al. , 2006 ) could be tailored to our peer-review domain , where the definition of helpfulness is largely influenced by the educational context of peer review . While previously we used the average of two expert-provided ratings as our gold standard of peer-review helpfulness1 , there are other types of helpfulness rating ( e.g. author perceived helpfulness ) that could be the gold standard , and that could potentially impact the features used to build the helpfulness model .
In our prior work ( @@CITATION ) , we examined whether techniques used for predicting the helpfulness of product reviews ( Kim et al. , 2006 ) could be tailored to our peer-review domain , where the definition of helpfulness is largely influenced by the educational context of peer review .