Computation, Logic and Algebra of information for the Multispace Society

Distributed computational systems have changed substantially in the recent past with the advent of technologies such as Social Networks and Cloud Storage. What marks these systems is an emphasis on the flow of epistemic information (facts, beliefs, lies) to a much greater degree than before with great impact on our democracy and on our society at large. A compelling example involving privacy threats and group polarization is the Facebook–Cambridge Analytica data scandal where private information of at least 87 millions of users was collected without their consent. This information could have been potentially used to build psychological profiles of users and then for psychographic microtargeting to influence the 2016 general election campaign. It is not clear that a substantial number users would have changed their minds on voting for a given candidate. Nevertheless, microtargeting may reinforce users’ preconceived notions and beliefs. This contributes to group polarization, making the opinions and beliefs of the users of a given group more extreme than the initial inclinations of its members. This clearly may have affect civil discourse with negative effects for the electoral process and democracy at large. We can single out two prominent aspects from the above-mentioned systems that are central to this proposal; to the best of our knowledge, they have not been sufficiently addressed in the context of concurrency theory for social media. The first one is the intrinsic epistemic nature of these systems arising from the presence of social behavior. We constantly have millions of users posting and learning facts, opinions, beliefs, lies and making decisions on social networks; epistemic information is everywhere. How precisely and by whom a user's opinions and beliefs can be seen may have a significant impact on his social/professional life or that of his affiliations (companies, governmental bodies, etc). We would also like to decide whether a given post or intentional lie may lead to group polarization, public announcements of sensitive information or affect decision-making. Being able to model this epistemic flow in a highly distributed environment would thus be an important contribution to assessing social risks. Social networks may facilitate civil discourse by making possible a prompt exchange of facts, beliefs and opinions among members of a community (known as circles, groups, friends). Nevertheless, because of their popularity and computational nature, social networks are also exposed to actors (algorithms, malicious agents, etc) that can direct and filter specific information to millions of users based on their social media history such as posts, searches and group affiliations. Even if not intentional, this may result in an extreme polarization of opinions as people with opposing views would tend to interpret new information in a biased way causing their views to move further apart [11]. Similarly, a group with uniform views often tends to make more extreme decisions than its individuals [10]. As a result, users’ beliefs may become more radical and isolated in their own ideological circle causing dangerous splits in society [12]. The situation becomes even more complex when the pieces of information directed at users are intentional lies, hoaxes or fake news. Indeed, social media platforms have played a key role in the political process. Referenda such as Brexit and the Colombian Peace Agreement as well as the USA 2016 Presidential Election are compelling examples of this phenomenon [9]. These cases illustrated that messages in social media with elements of extremist ideology in political and public discourse, lies, misleading or malicious information (fake news), demagoguery and ethnic discrimination may influence fundamental decision-making processes. In fact, we have reached a critical point where the production of malicious information in social media by fake news websites has become a profitable source of revenue in some countries like Macedonia [8]. Distributed computational systems have changed substantially in the recent past with the advent of technologies such as Social Networks and Cloud Storage. What marks these systems is an emphasis on the flow of epistemic information (facts, beliefs, lies) to a much greater degree than before with great impact on our democracy and on our society at large.