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The aim of the text is to reflect on the formation of the so-called digital echo chambers or filter bubbles, which are environments formed around particular topics whose objective is to promote a given political-ideological position. The argument the author puts forward is that echo chambers are social systems of interaction created to deal with the process of informational overload brought about by the consolidation of digital media in people’s daily lives.

The author used Niklas Luhmann’s theory of social systems to explain what the author is calling social systems of interaction. Furthermore, the author made clarifications about: (1) the current debate regarding echo chambers; (2) what is the concept of “information” that the author is using to formulate the proposition and (3) what is the specificity that digital media bring when the author talks about informational overload and about the formation of echo chambers.

The author concluded that echo chambers can be seen as digital interaction systems, but the concept of “interaction” must be adapted. The author also concluded that echo chambers help society to deal with the phenomenon of informational overload.

There are few works which try to make a detailed analysis of echo chambers from a Luhmannian perspective. With the propositions presented in this text, along with other writings of the own, the author gives an important step in that direction by introducing the topic in the social systems researchers community.

There is a growing worry about people possibly isolating themselves in online bubbles and avoiding contact with ideas that differ from their beliefs, creating a scenario of ideological polarization. To investigate into this matter, this work aims for a reflection about the contingency of communication in social media. Does social media make the experience of communication in the digital space more contingent (providing it with more possibilities, with people accessing different contents and ideas) or less contingent (reducing the available possibilities, making people isolate themselves)?

This is a theoretical work, constructed through bibliographical reviews. To reflect about the question that are posed, the author selected Niklas Luhmann's social systems theory to approach the concept of contingency. In addition to that, the author presented the main arguments of the debates about echo chambers and online bubbles. In the end, the author combined the two reviews together using elements of the Luhmannian theory and drew some conclusions about the initial question.

The study concluded that social media have an ambivalent potential regarding contingency in the digital space: it can both expand or reduce the available possibilities of communication, depending on criteria like topic, potential of diffusion and focus of attention. There is no one-side effect.

The approach at echo chambers does not reflect “the” form of contingency in social media, but “a” form. Therefore, the study cannot provide any general conclusions about the relation between contingency and social media. The digital space is a large one, and more studies are required to achieve more substantial propositions.

The research has an originality value both for systems theory and social media studies. First, because, as far as the author knows, no other system-theoretical argument has taken the connection between contingency and social media as a primary analysis object. Second, because of a theoretical interpretation effort, the studies of echo chambers indicate mixed results about the phenomenon of online isolation, but no attempt was made to make sense of these mixed results from a specific sociological theory. The author did that by using Luhmann's theoretical framework, which proved to be a good tool for explaining and unifying these different results on a more abstract level.

In this study, we aimed at examining the unique and interactive effects of peer violence in cyberspace on adolescents’ emotion regulation and socioemotional adjustment, as well as the mediational role of resilience in the link between adolescent’s pathogenic relational experiences and behavioral outcomes. Specifically, we intended to explore emotion differentiation and regulation in reaction to bullying perpetration and victimization and in terms of positive (proud, confident, good) and negative (ashamed, excited, guilty), Passive (sad, embarrassed, humiliated) and Reactive (angry, scared) emotions and how it impacted and predicted positive and negative outcomes.

A stratified convenient sample of 494 Italian students aged 13–19 years (M = 15.27, SD = 1.23) was selected to represent all different school types in Italy and the students were administered a self-report questionnaire on school bullying involvement. General Linear Models, ANOVA, and T-tests were employed to explore gender differences, the relationships between variables, and their contribution to the predictive model. A two-step Cluster analysis was used to profile adolescents based on patterns of resilience, health outcomes, and cyberbullying involvement.

Results showed significant gender differences, with females using internet and Facebook more than males and being more resilient, positive, and prosocial, but also responding to victimization with higher levels of alienation, anger, humiliation, and psychosomatic and emotional symptoms. Males perpetrated peer violence more than females, were less likely to be victimized, and were generally less emotionally impacted by it. Victimization rates (63.7%, n = 296) were higher than perpetration rates (51.7%, n = 233) and bully-victimization was prevalent (47.1%). Victims prevalently experienced passive emotions (sadness, humiliation, embarrassment) while perpetrators experienced negative ones (guilt and shame). Cluster analysis evidenced different pathways and trajectories of resilience and cyberbullying involvement: Resilient victims (RV), Healthy uninvolved (HU), Healthy Bullies (HB), Alienated Bully-Victims (ABV), and Resilient Bully-Victims (RBV). RV, HU, and HB resulted all well-adjusted, despite the different involvement in cyberbullying, and also RBV and despite the double involvement in cyberbullying, ABV were the only maladjusted and at-risk group in our sample characterized by very low Positivity, very low Resilience, and extremely high Alienation.

This study proposes a comprehensive, developmental, ecological, relational, and self-regulatory resilience approach to cyberbullying, which represents an innovative and advanced contribution to the literature with significant implication for research and practice. Fully understanding and measuring the emotional impact of cyber peer violence and resilience following cyberbullying victimization and perpetration can help in developing targeted interventions for both victims and bullies. This study highlighted the need for a self-regulatory model of resilience for modulating emotions, arousal, and behaviors across contexts, relationships, and difficulties. It also evidenced that moderate levels of resilience and positivity are sufficient to buffer youth from involvement in cyberbullying and to predict healthy adjustment and less pathological outcomes.

By profiling adolescents based on resilience levels, health outcomes, and cyberbullying involvement, we evidenced five distinct trajectories of risk evaluation for cyberbullying beyond participating roles. Our results confirmed the fundamental importance of assessing resilience and emotion regulatory resources together with peer violence involvement in identifying and targeting adolescents at risk.

This purpose of this paper is to propose a novel hybrid genetic algorithm based on a virtual machine (VM) placement method to improve energy efficiency in cloud data centers. How to place VMs on physical machines (PMs) to improve resource utilization and reduce energy consumption is one of the major concerns for cloud providers. Over the past few years, many approaches for VM placement (VMP) have been proposed; however, existing VM placement approaches only consider energy consumption by PMs, and do not consider the energy consumption of the communication network of a data center.

This paper attempts to solve the energy consumption problem using a VM placement method in cloud data centers. Our approach uses a repairing procedure based on a best-fit decreasing heuristic to resolve violations caused by infeasible solutions that exceed the capacity of the resources during the evolution process.

In addition, by reducing the energy consumption time with the proposed technique, the number of VM migrations was reduced compared with existing techniques. Moreover, the communication network caused less service level agreement violations (SLAV).

The proposed algorithm aims to minimize energy consumption in both PMs and communication networks of data centers. Our hybrid genetic algorithm is scalable because the computation time increases nearly linearly when the number of VMs increases.

Direct care staff may be resistant to the use of behavioural interventions. Whilst some research suggests that resistance to the cost of behavioural interventions is one factor of influence, there is lack of research exploring why staff are influenced by the cost. The purpose of this paper is to explore this issue.

In this paper, the phenomenon of resistance is analysed with the help of behavioural economics and of the behavioural perspective model (BPM).

The resistance to the cost of behavioural interventions is correlated with the low quality of the working environment and ways in which staff might attend to factors which protect their own well-being.

Services might need to focus on the ways in which behavioural interventions protect staff’s well-being.

This paper explores the use of the BPM and of behavioural economics as conceptual tools for the analysis of the factors leading to non-adoption of behavioural interventions.