Aara' - A system for mining the polarity of Saudi public opinion through e-newspaper comments

Abstract

Aara' is a system for mining opinion polarity through the pool of comments that readers write anonymously at the online edition of Saudi newspapers. We use a nave Bayes classifier with a revised n-gram approach to extract the public opinion polarity, which is expressed in Arabic, classifying it into four categories. For training we manually marked the comments as belonging to one of the categories. All the words in the documents of the training set were removed except those with explicit connotations. After the training the words designated as vocabulary were classified into one of the categories. Our system carries out polarity classification over informal colloquial Arabic that is unstructured and with a reasonable proportion of spelling errors. The result of testing our system showed a macro-averaged precision of 86.5%, while the macro-averaged F-score was 84.5%. The accuracy of the system is 82%. © The Author(s) 2014.