Symmetric Multi-Aspect Evaluation of Comments

As we explained in [3], most online systems for the Social Web, such as social media, online discussion forums, news sites and product review sites, offer limited support in identifying the helpful comments among the credible ones. We thus proposed the multiDimensional Comment Evaluation (mDiCE) framework, which relies on methodologies from the field of Computational Argumentation to clearly distinguish between the acceptance (credibility) and the quality (helpfulness) of arguments. In this paper, we extend this framework and introduce the symmetric multi-Dimensional Comment Evaluation (s-mDiCE) framework, which has a more intuitive behavior and a wider scope, aiming to cover also the goal-oriented debates found in decision support systems or in debate portals, e.g., in active citizenship portals. s-mDiCE combines features, such as voting on arguments, expert rating, supporting and attacking arguments, in a unified and adaptable framework that can guarantee intuitive behavior for the user or the moderator who wish to spot important opinions or to rank them for easier processing.