MOOD: Massive Open Online Deliberation Platform-A Practical Application
E.P. Verdiesen (TU Delft - Information and Communication Technology)
Virginia Dignum (TU Delft - Information and Communication Technology)
Jeroen van den Hoven (TU Delft - Values Technology and Innovation)
Martijn Cligge (Student TU Delft)
Jan Timmermans (Student TU Delft)
Lennard Segers (Student TU Delft)
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Abstract
Nowadays, public debates often take place on social media platforms like Facebook or Twitter and can be characterized as asynchronous, protracted and ill-structured. The Massive Open Online Deliberation (MOOD) platform aims to structure these debates. Essential is that the platform can differentiate between the moral acceptability and the social acceptance of a debate outcome. We briefly describe the e-deliberation process and look at two existing debate platforms, Liquidfeedback and Debatehub. We design and build a prototype that mainly focuses on:(1) a method to differentiate and validate facts and opinions, and (2) a mechanism that maps both the social acceptance and the moral acceptability of debate outcomes. We research these ethical concepts more in depth and implement several techniques, such as a voting mechanism, in a working prototype that supports a four stage deliberation process. In future applications, machine learning techniques can be integrated in the platform to perform sentiment analysis on a debate.