Dynamics of deceptive interactions in social networks

In this paper we examine the role of lies in human social relations by implementing some salient characteristics of deceptive interactions into an opinion formation model, so as to describe the dynamical behaviour of a social network more realistically. In this model we take into account such basic properties of social networks as the dynamics of the intensity of interactions, the influence of public opinion, and the fact that in every human interaction it might be convenient to deceive or withhold information depending on the instantaneous situation of each individual in the network. We find that lies shape the topology of social networks, especially the formation of tightly linked, small communities with loose connections between them. We also find that agents with a larger proportion of deceptive interactions are the ones that connect communities of different opinion, and in this sense they have substantial centrality in the network. We then discuss the consequences of these results for the social behaviour of humans and predict the changes that could arise due to a varying tolerance for lies in society.Comment: 17 pages, 8 figures; Supplementary Information (3 pages, 1 figure

Modeling technological change on telecenter effectiveness

Technological change (TC) is the overall process of continuous invention, innovation and diffusion of technology that aims at improving the quality of technical performance. Without TC, there would be no business growth and development particularly in a telecenter. A telecenter is public environments that people develop essential digital skills to access information and communications technologies to create, learn and achieve their specific needs. The major goal of a telecenter is to bridge the digital gap between the urban and the rural areas, and provide digital support services to the neighbouring community. Telecenter effective usage is a major issue of telecenter sustainability because it has been found that there a lack of usage. Hence, this study focused on identifying TC factors that contribute significantly to telecenter effectiveness. The first objective of the study was to identify the contributing factors of TC. The second objective was to construct a computational model based on selected factors obtained from objective 1. The third objective was to evaluate the effectiveness of the model. The research was conducted using the computational model approach through three phases: abstraction, formlization, and evaluation. The results showed that the computational model was able to show the effect of the selected TC on telecenter effectiveness in different types of scenarios. The usage of telecenter can be more effective by considering the TC factors that are appropriate

Trust and distrust in contradictory information transmission

We analyse the problem of contradictory information distribution in networks of agents with positive and negative trust. The networks of interest are built by ranked agents with different epistemic attitudes. In this context, positive trust is a property of the communication between agents required when message passing is executed bottom-up in the hierarchy, or as a result of a sceptic agent checking information. These two situations are associated with a confirmation procedure that has an epistemic cost. Negative trust results from refusing verification, either of contradictory information or because of a lazy attitude. We offer first a natural deduction system called SecureNDsim to model these interactions and consider some meta-theoretical properties of its derivations. We then implement it in a NetLogo simulation to test experimentally its formal properties. Our analysis concerns in particular: conditions for consensus-reaching transmissions; epistemic costs induced by confirmation and rejection operations; the influence of ranking of the initially labelled nodes on consensus and costs; complexity results

Trust and distrust in contradictory information transmission

We analyse the problem of contradictory information distribution in networks of agents with positive and negative trust. The networks of interest are built by ranked agents with different epistemic attitudes. In this context, positive trust is a property of the communication between agents required when message passing is executed bottom-up in the hierarchy, or as a result of a sceptic agent checking information. These two situations are associated with a confirmation procedure that has an epistemic cost. Negative trust results from refusing verification, either of contradictory information or because of a lazy attitude. We offer first a natural deduction system called SecureNDsim to model these interactions and consider some meta-theoretical properties of its derivations. We then implement it in a NetLogo simulation to test experimentally its formal properties. Our analysis concerns in particular: conditions for consensus-reaching transmissions; epistemic costs induced by confirmation and rejection operations; the influence of ranking of the initially labelled nodes on consensus and costs; complexity results

THE SOCIAL FROM THE ECONOMIC: THE EMERGENCE OF SOLIDARITY WITHIN NETWORKS OF ECONOMIC EXCHANGE

In this dissertation, we attempted to contribute to the discussion about the link between the economic and the social. More specifically, we addressed the debate on the consequences of economically-oriented interaction on social relations. Sociological studies have mostly focused on understanding the opposite direction, i.e., the effect of social relations on economic outcomes. Conversely, our work was motivated by the idea that the consequences of the economic on the social is crucial for social sciences and society in general. First, we reviewed the literature on solidarity and exchange relations in sociology and the behavioural sciences. The chapter aimed to elaborate a theoretical framework and working hypotheses for the following chapters. We proposed a definition of solidarity at the behavioural level and various empirical contributions have been examined. Next, we conducted an empirical study on the link between professional collaboration and social support relations. In this work, certain hypotheses were tested on a group of independent professionals sharing a \u2019coworking\u2019 space. Here, we found that solidarity can emerge as a by-product of economic exchange among strangers if they are allowed to select each other for collaboration and develop trust relations. The following chapter presents an extensive literature review of the use of Agent-Based Models (ABM) for sociological research. Given the key role of this methodology in this dissertation, the chapter aims to provide a comprehensive account of the contributions to sociology given by applications of ABM computer simulations. Moreover, a classification of these contributions is proposed according to the various methodological approaches to ABM in social research. The aim of the chapter is to review ABM as a possible means to overcome some limitations of the study presented before. Then, the final study applies computer simulation to analyze cohesion and integration of a social support network from economic exchange. In this chapter, an ABM of the mechanisms observed in the previous empirical study is presented. The model is used to simulate the effect of competition and resource distribution on social support networks. The aim of this work is to explore the effects of different environmental conditions and overcome the context-specific properties of empirical data. We argue that competition over most attractive collaborators can undermine the emergence of a cohesive social support network. Yet, this detrimental effect can be avoided if we assume that poor-resource actors are more eager to ask others for support, therefore generating a cohesive and more integrated social support network. Finally, we drew some conclusions in the last chapter