Causality in Collective Filtering

Abstract

In this paper, we describe a proposal for improving the practice of web-based collective filtering, in particular for what regards discussions and selection of issues about policy, based on the intuitive concept of causality. Causality, especially when presented in visual form, is especially suited to the task since it is intuitive to understand and to use, and at the same time, it's rich enough to create a semantic network between the representations of real world facts. We give some examples of the suggested system workflow and we present guidelines for its implementation.

Keywords: Causality, Crowdsourcing