This paper examines the interplay of opinion exchange dynamics and communication network formation. An opinion formation procedure is introduced which is based on an abstract representation of opinions as k-dimensional bit-strings. Individuals interact if the difference in the opinion strings is below a defined similarity threshold dI . Depending on dI , different behaviour of the population is observed: low values result in a state of highly fragmented opinions and higher values yield consensus. The first contribution of this research is to identify the values of parameters dI and k, such that the transition between fragmented opinions and homogeneity takes place. Then, we look at this transition from two perspectives: first by studying the group size distribution and second by analysing the communication network that is formed by the interactions that take place during the simulation. The emerging networks are classified by statistical means and we find that non-trivial social structures emerge from simple rules for individual communication. Generating networks allows to compare model outcomes with real-world communication patterns.Such an abstract bit-string approach has been used in the simulation of consumer-producer behaviour [6] as well as in the context of labour market analysis [5] where bit-strings represent products (or job offers) and needs (worker skills). Here, each bit-string represents an agent opinion and a procedure of agent-agent interaction is specified based on assumptions from social comparison theory [15] and in opinion formation models [7,12,3,26,27].This paper is organized in the following way. We start reviewing previous approaches to the modelling of opinion exchange dynamics. After this, we give an explanation of our model. This is followed by a numerical analysis, in which the opinion evolution is considered before looking at the emerging networks of communication activity. A discussion of the results concludes this work.1 Behaviour classes refer to qualitative different behaviours that potentially result from a simulation model.

Political terrorism and insurgency have become the primary means of global war among states. Lacking comparable military and political means to compete directly with Western civilization, many failed states and tribes have honed the art of asymmetric warfare. But traditional models of organizations do not work under normal or these extreme circumstances, precluding realistic models of terrorism and a fruitful search among alternatives for potential solutions. In contrast to traditional models, we have made substantial progress with a quantum model of organizations, which we further develop in this study with the introduction of a case study of a normal organization in the process of being restructured. We apply preliminary results from our model to terrorist organizations and counter terrorism.

We introduce an agent-based model describing a susceptible-infectious-susceptible (SIS) system of humans and mosquitoes to predict malaria epidemiological scenarios in realistic biological conditions. Emphasis is given to the transition from endemic behavior to eradication of malaria transmission induced by combined drug therapies acting on both the gametocytemia reduction and on the selective mosquito mortality during parasite development in the mosquito. Our mathematical framework enables to uncover the critical values of the parameters characterizing the effect of each drug therapy. Moreover, our results provide quantitative evidence of what is empirically known: interventions combining gametocytemia reduction through the use of gametocidal drugs, with the selective action of ivermectin during parasite development in the mosquito, may actively promote disease eradication in the long run. In the agent model, the main properties of human-mosquito interactions are implemented as parameters and the model is validated by comparing simulations with real data of malaria incidence collected in the endemic malaria region of Chimoio in Mozambique. Finally, we discuss our findings in light of current drug administration strategies for malaria prevention, that may interfere with human-to-mosquito transmission process.

Conflicts involving caste issues, mainly concerning the lowest caste rights, pervade modern Indian society. Caste affiliation, being rigorously enforced by the society, is an official contemporary reality. Although caste identity is a major social discrimination, it also serves as a necessary condition for affirmative action like reservation policy. In this article, we perform an original and rigorous analysis of the discourse involving the theme “caste” in India newspapers. To this purpose, we have implemented a computational analysis over a big dataset of the 2016 and 2017 editions of three major Indian newspapers to determine the most salient themes associated with “caste” in the news. We have used an original mix of state-of-the-art algorithms, including those based on statistical distributions and two-layer neural networks, to detect the relevant topics in the news and characterize their linguistic context. We concluded that there is an excessive association between lower castes, victimization, and social unrest in the news that does not adequately cover the reports on other aspects of their life and personal identity, thus reinforcing conflict, while attenuating the vocality and agency of a large section of the population. From our conclusion, we propose a positive discrimination policy in the newsroom.

Abstract. Education is a major force for economic and social wellbeing. Despite high aspirations, education at all levels can be expensive and ineffective. Three Grand Challenges are identified: (1) enable people to learn orders of magnitude more effectively, (2) enable people to learn at orders of magnitude less cost, and (3) demonstrate success by exemplary interdisciplinary education in complex systems science. A ten year 'man-on-the-moon' project is proposed in which FuturICT's unique combination of Complexity, Social and Computing Sciences could provide an urgently needed transdisciplinary language for making sense of educational systems. In close dialogue with educational theory and practice, and grounded in the emerging data science and learning analytics paradigms, this will translate into practical tools (both analytical and computational) for researchers, practitioners and leaders; generative principles for resilient educational ecosystems; and innovation for radically scalable, yet personalised, learner engagement and assessment. The proposed Education Accelerator will serve as a 'wind tunnel' for testing these ideas in the context of real educational programmes, with a e-mail: j.h.johnson@open.ac.uk 216The European Physical Journal Special Topics an international virtual campus delivering complex systems education exploiting the new understanding of complex, social, computationally enhanced organisational structure developed within FuturICT.