RA-SR: Using a ranking algorithm to automatically building resources for subjectivity analysis over annotated corpora

In this paper we propose a method that uses corpora where phrases are annotated as Positive, Negative, Objective and Neutral, to achieve new sentiment resources involving words dictionaries with their associated polarity. Our method was created to build sentiment words inventories based on sentisemantic evidences obtained after exploring text with annotated sentiment polarity information. Through this process a graph-based algorithm is used to obtain auto-balanced values that characterize sentiment polarities well used on Sentiment Analysis tasks. To assessment effectiveness of the obtained resource, sentiment classification was made, achieving objective instances over 80%.