Causality in Collective Filtering

12 Pages Posted: 21 May 2011

See all articles by Mario Paolucci

Mario Paolucci

Italian National Research Council (CNR) - Institute of Cognitive Sciences and Technologies (ISTC)

Stefano Picascia

Laboratory of Agent Based Social Simulation (LABSS)

Walter Quattrociocchi

IMT Lucca

Date Written: May 19, 2011

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

Suggested Citation

Paolucci, Mario and Picascia, Stefano and Quattrociocchi, Walter, Causality in Collective Filtering (May 19, 2011). Available at SSRN: https://ssrn.com/abstract=1846575 or http://dx.doi.org/10.2139/ssrn.1846575

Mario Paolucci (Contact Author)

Italian National Research Council (CNR) - Institute of Cognitive Sciences and Technologies (ISTC) ( email )

Via Palestro, 32
Roma, RM 00185
Italy

Stefano Picascia

Laboratory of Agent Based Social Simulation (LABSS) ( email )

via Palestro 32
Roma, 00195
Italy

Walter Quattrociocchi

IMT Lucca ( email )

Lucca
Italy
3392922276 (Phone)

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