What's public feedback? Linking high quality feedback to social issues using social media

In this paper we present a study of new problem of linking high quality public feedback to the issues discussed in an article. Analyzing public opinion on social and political issues as well as government policies is of particular importance to policy makers. Given a segmented article with multiple issues and public comments towards the article, the task aims to extract high quality feedback and link it to the relevant issues in the article. Our proposed solution, two-stage approach rely on supervised learning technique for extracting high quality feedback and statistical topic modeling technique for extracting the relevant feedback to the issues/topics of the article. We study the problem on two different data sets. We evaluated both the stages of the framework and the empirical results on both data sets show that the proposed approach is effective in linking high quality relevant feedback to the segments of the article.