Social Honesty Research Articles

The Social Honesty game - A computational analysis of the impact of conformity and identity on honest behavior contagion in complex social systems

Abstract We consider a probabilistic-payoff social dilemma game and we analyze the impact of various social learning mechanisms - conformity, diversity generators, identity, on the dynamics of honest behavior in a virtual population. To capture the inherent variability and uncertainty of a complex social environment, the proposed model considers probabilistic payoffs as well as a variety of strategy updating rules and hybrid neighborhood topologies. The implicit underlying mechanisms are those of imitation and social influence. By simulating evolutionary spatial scenarios, we identify factors that favor contagion of honest behavior (i.e. social honesty) in the context of probabilistic payoff. Conformity and identity have a significant effect on the contagion of honest behavior. They slow down the dynamics, make it more stable, and help the formation and growth of clusters, favoring the emergence and spreading of honest behavior. However, their impact is topology dependent, nonlinear, exhibiting phase shifts. High conformity favors honest behavior in simple topologies, and does the opposite in complex topologies. Without a certain degree of diversity (use of alternative strategies) the system loses its adaptation capability. At the other end, strategy inconsistency leads to chaos, which favors the contagion of dishonest behavior. A structuring effect of leaders on chaotic behavior is also observed: their presence reduces the effects of random behavior, inducing alignment and reducing the necessity of a higher punishment probability. The key findings of this research can help predict trends and design public and organizational policies to nudge honest behavior, in the context of high complexity dynamics generated by the recent advances in information technology.

Naturalness in the production of vegetable oils and proteins

The crushing industry is called upon to modify its processing methods in response to a rising demand for vegetable proteins, while at the same time increasing transparency and naturality. Changing the processes without taking this request into account would mean risking rejection and failure. The social sciences have shown that the collective unconscious inextricably links the notion of naturalness to healthy eating, respect for the environment, and social honesty. However, this notion goes beyond what’s rational and proves difficult to pin down when it comes to evaluating products. France does not recognize the ISO data sheet that defines what a “natural” ingredient is. Yet we do need a standard, if only to make informed choices between different possible technological paths. This standard of reference could be inspired by available norms in related fields, or it could be based on the best available technologies within a framework that takes into account both societal aspirations and the technical and economic possibilities of the industrial world. To achieve this, the sector’s representative bodies, the State, and consumer advocate groups should engage in a collective approach.

A Novel Methodology for designing Policies in Mobile Crowdsensing Systems

Mobile crowdsensing is a people-centric sensing system based on users’ contributions and incentive mechanisms aim at stimulating them. In our work, we have rethought the design of incentive mechanisms through a game-theoretic methodology. Thus, we have introduced a multi-layer social sensing framework, where humans as social sensors interact on multiple social layers and various services. We have proposed to weigh these dynamic interactions by including the concept of homophily, that is a human-related factor related to the similarity and frequency of interactions on the multiplex network. We have modelled the evolutionary dynamics of sensing behaviours by defining a mathematical framework based on multiplex EGT, quantifying the impact of homophily, network heterogeneity and various social dilemmas. We have detected the configurations of social dilemmas and network structures that lead to the emergence and sustainability of human cooperation. Moreover, we have defined and evaluated local and global Nash equilibrium points by including the concepts of homophily and heterogeneity. Therefore, we have analytically defined and measured novel statistical measures of social honesty, QoI and users’ behavioural reputation scores based on the evolutionary dynamics. Through the proposed methodology we have defined the Decision Support System (DSS) and a novel incentive mechanism by operating on the policies in terms of users’ reputation scores, that also incorporate users’ behaviours other than quality and quantity of contributions. To evaluate our methodology experimentally, we consider a real dataset on vehicular traffic monitoring crowdsensing application, Waze, and we have derived the disbursement of incentives by also comparing our method with baselines. Experimental results demonstrate that our methodology, based on both quality and quantity of reports and the local or microscopic spatio-temporal distribution of behaviours, is able to better discriminate users’ behaviours. This multi-scale characterisation of users (both global and local) represents a novel research direction and paves the way for novel policies on mobile crowdsensing systems.

Talking About Dying: A Select Review

ABSTRACTThis review article argues that death has re-emerged as a topic of academic study across a number of disciplines, and that in popular culture death is now spoken about in a way that is both surprising and new and also re-connects us with an older social honesty about the human condition. The case is illuminated by a review of four books that have emerged during this renaissance of thinking about death and dying.

Community resilience and Chagas disease in a rural region of Mexico.

ABSTRACTOBJECTIVE To explore the pillars of community resilience in a region where Chagas disease is endemic, with the aim of promoting participatory processes to deal with this condition from the resilience of the population.METHODS Qualitative study using ethnographic record and six interviews of focus groups with young people, women and men. The research was carried out in a rural area of the state of Morelos, Mexico, between 2006 and 2007. We carried out educational sessions with the population in general, so that residents could identify the relationship between the vector Triatoma pallidipennis, the parasite (Trypanosoma cruzi), symptoms, and preventive actions for Chagas disease. The ethnographic record and groups were analyzed based on Taylor and Bogdan’s modification, and the focus was to understand the socio-cultural meanings that guide the speeches and activities of residents in relation to the pillars of community resilience.RESULTS The population felt proud of belonging to that location and three pillars of community resilience were clearly identified: collective self-esteem, cultural identity, and social honesty. Having these pillars as bases, we promoted the participation of the population concerning Chagas disease, and a Community Action Group was formed with young people, adult men and women, and social leaders. This Group initiated actions of epidemiological and entomological surveillance in the community to deal with this problem.CONCLUSIONS It is necessary to create more experiences that deepen the understanding of the pillars of community resilience, and how they contribute to enhance participation in health to deal with Chagas disease.

A Strategic Interaction Model of Punishment Favoring Contagion of Honest Behavior

The punishment effect on social behavior is analyzed within the strategic interaction framework of Cellular Automata and computational Evolutionary Game Theory. A new game, called Social Honesty (SH), is proposed. The SH game is analyzed in spatial configurations. Probabilistic punishment is used as a dishonesty deterrence mechanism. In order to capture the intrinsic uncertainty of social environments, payoffs are described as random variables. New dynamics, with a new relation between punishment probability and punishment severity, are revealed. Punishment probability proves to be more important than punishment severity in guiding convergence towards honesty as predominant behavior. This result is confirmed by empirical evidence and reported experiments. Critical values and transition intervals for punishment probability and severity are identified and analyzed. Clusters of honest or dishonest players emerge spontaneously from the very first rounds of interaction and are determinant for the future dynamics and outcomes.