**2. Theoretical concept**

The HELIOSPHERE is an inclusive, transparent and fair debating platform that addresses the lack of trust in public, online and offline debates to support the democratic process of modern society. It implements an easy-to-apply solution that can be used in any public setting, whether entirely online or as a hybrid concept, both offline and online and with minimal effort. The main component about trust is the AI-supported real-time debate analytics solution, which supports both the moderation and the offline/online audience in identifying and adjusting to elements of debates that create bias, manipulation, monopolisation etc. Participants can share, design and validate the debate with relevant content. HELIOSPHERE utilises Machine Learning models trained on datasets collected from already held debates and speeches that enable the debate to become more transparent and fairer and data gathered from media, political and other resources (see below the data engine section). The platform is not limited to a particular language, border limitations. It includes multilingual real-time modules, Cross-Border Content Rights, Data Privacy embedded from the start, Freedom of Speech to understand how meaningful debates can increase the trust in the political and democratic communication process in modern society.

In other words, public debates can be considered a remedy to political distrust. Studies focused on how such debates can promote social learning [8], change the

#### *Computer-Mediated Communication*

participant's preferences [9]. This type of debate is viewed as the most advanced method to institutionalise deliberative democracy [10].

To increase transparency, inclusiveness and fairness during the debate, the HELIOSPHERE visualisation focuses on the following analytics results:


Sensible guidelines support moderators in making fair use of this information to ensure that they will increase fairness and reason throughout the debate rather than making it easier for any speaker to win an argument through clever manipulation. The HELIOSPHERE system will continue to learn and monitor the topic's coverage and identify when the time has come to re-open the debate or have a new debate on the subject based on significant recent developments. In the following sections, we describe the platform architecture and its components.
