Increasingly, activities in work and social life are conducted within human-machine networks, where collaboration involves many different actors; governments and organisations, individuals and machines such as smart devices, sensors and computing infrastructure. The targets of these networks can be for policy making, commercial innovation, education, improved quality of life, information exchange or resource organisation. As networks become more complex and include more connections between humans and machines, so the characteristics of those networks become important in determining the effectiveness and successful evolution of the collaborations which they support. Emerging challenges are: understanding the processes necessary for developing and maintaining human-machine networks such that they are able to deliver their intended outcomes; and applying this knowledge to support emerging networks in public, commercial and civil domains to more readily achieve key European goals. In HUMANE we will develop a typology of human-machine networks focused on characteristics of relationships between networked humans and machines such as trust, motivation, reputation, responsibility, privacy and security. We will consider health indicators for networks and create prototype tools that can be exploited through a community of stakeholders to create and enrich human-machine networks. We will propose a roadmap and methodology for the evolution of such networks, appropriate to the needs of ICT developers, building on in-depth case studies taken from R&I projects relevant to the societal DAE pillars to form a supporting framework for future thinking and ICT policy-making in Europe. The project partners in HUMANE have wide and complementary experience in social sciences and ICT R&I, essential for bridging the technological, societal, industrial and human-centric components necessary to achieve improved understanding of emerging hyper-connected human-machine networks.

An exponential increase in the use of social media has accelerated information diffusion. Disinformation also spreads, often faster and more widely than true news, posing a risk for democracy, national security, and social fabric, and undermining society’s trust in the information. It is therefore necessary to understand and measure the impacts of disinformation on opinions, culture, policy, and profits, as well as develop specific tools and services to allow citizens and the professional community to understand Social Media correctly. The SOMA (Social Observatory for Disinformation and Social Media Analysis) project aims to provide a springboard for the social media sector to steer an understanding of its dynamics and the relationship between social media and other sectors. SOMA will: map European social media actors by using an open community-based mapping service; establish a European centre for social media stakeholders undertaking research on disinformation; and, develop a Source Transparency Index to immediately verify sources. Key proposed solutions are: (i) a platform for content verification; (ii) fact-checking tools; (iii) social media mapping and visualisation tools for the engagement of European Social Media Innovation initiatives and EU projects. SOMA will also: (iv) develop a methodology for the socio-economic impact assessment of disinformation; (v) provide strategies and actions to increase media literacy, analyse legal roadblocks and community-based self-regulation aspects; (vi) provide policy recommendations based on the analysis of the information collected by the Observatory; (vii) develop tools for community-mapping and an analysis of a future hyper-connected society; (viii) create a repository of disinformation-related knowledge. The overall expected impact by SOMA is the creation of a solid environment to increase awareness among stakeholders on social media topics and develop tools and instruments for the social media community.