Bistability through triadic closure

We propose and analyse a class of evolving network models suitable for describing a dynamic topological structure. Applications include telecommunication, on-line social behaviour and information processing in neuroscience. We model the evolving network as a discrete time Markov chain, and study a very general framework where, conditioned on the current state, edges appear or disappear independently at the next timestep. We show how to exploit symmetries in the microscopic, localized rules in order to obtain conjugate classes of random graphs that simplify analysis and calibration of a model. Further, we develop a mean field theory for describing network evolution. For a simple but realistic scenario incorporating the triadic closure effect that has been empirically observed by social scientists (friends of friends tend to become friends), the mean field theory predicts bistable dynamics, and computational results confirm this prediction. We also discuss the calibration issue for a set of real cell phone data, and find support for a stratified model, where individuals are assigned to one of two distinct groups having different within-group and across-group dynamics

Associative nature of event participation dynamics: a network theory approach

The affiliation with various social groups can be a critical factor when it comes to quality of life of each individual, making such groups an essential element of every society. The group dynamics, longevity and effectiveness strongly depend on group's ability to attract new members and keep them engaged in group activities. It was shown that high heterogeneity of scientist's engagement in conference activities of the specific scientific community depends on the balance between the numbers of previous attendances and non-attendances and is directly related to scientist's association with that community. Here we show that the same holds for leisure groups of the Meetup website and further quantify individual members' association with the group. We examine how structure of personal social networks is evolving with the event attendance. Our results show that member's increasing engagement in the group activities is primarily associated with the strengthening of already existing ties and increase in the bonding social capital. We also show that Meetup social networks mostly grow trough big events, while small events contribute to the groups cohesiveness.Comment: 16 pages, 6 figs + Supporting information 7 pages, 8 fig

Facility Location in Evolving Metrics

Understanding the dynamics of evolving social or infrastructure networks is a challenge in applied areas such as epidemiology, viral marketing, or urban planning. During the past decade, data has been collected on such networks but has yet to be fully analyzed. We propose to use information on the dynamics of the data to find stable partitions of the network into groups. For that purpose, we introduce a time-dependent, dynamic version of the facility location problem, that includes a switching cost when a client's assignment changes from one facility to another. This might provide a better representation of an evolving network, emphasizing the abrupt change of relationships between subjects rather than the continuous evolution of the underlying network. We show that in realistic examples this model yields indeed better fitting solutions than optimizing every snapshot independently. We present an $O(\log nT)$-approximation algorithm and a matching hardness result, where $n$ is the number of clients and $T$ the number of time steps. We also give an other algorithms with approximation ratio $O(\log nT)$ for the variant where one pays at each time step (leasing) for each open facility

Self-Segregation vs. Clustering in the Evolutionary Minority Game

Complex adaptive systems have been the subject of much recent attention. It is by now well-established that members (`agents') tend to self-segregate into opposing groups characterized by extreme behavior. However, while different social and biological systems manifest different payoffs, the study of such adaptive systems has mostly been restricted to simple situations in which the prize-to-fine ratio, $R$, equals unity. In this Letter we explore the dynamics of evolving populations with various different values of the ratio $R$, and demonstrate that extreme behavior is in fact {\it not} a generic feature of adaptive systems. In particular, we show that ``confusion'' and ``indecisiveness'' take over in times of depression, in which case cautious agents perform better than extreme ones.Comment: 4 pages, 4 figure

Sports Marketing and Branding among Gen Z and Their Digital Associations

This study addresses the intersection between sports marketing and branding among Generation Z, investigating the challenges, opportunities, and evolving dynamics in the digital realm. The problem at hand revolves around the intricate web of issues faced by athletes and stakeholders, including the implementation of Name, Image, and Likeness (NIL) rules, ethical considerations, and the transformative impact of social media. Background information was gathered from peer-reviewed literature. Using a qualitative research method, five participants from diverse sporting backgrounds provided insights through interviews. The participants were asked questions in a semi-formal setting about their personal experiences, background and understanding, education on these topics, ethical and legal considerations, impact on underrepresented groups, challenges, and future trends and predictions. The study illuminates the need for educational initiatives to empower athletes in navigating this digital landscape. Looking forward, the conclusion emphasizes the continued growth of sports marketing through social media. As Generation Z shapes the future of sports engagement, this study provides a snapshot of the current landscape while paving the way for future explorations into the evolving dynamics of sports marketing in the digital age

Simulating the Effect of Social Influence on Decision-Making in Small, Task-Oriented, Groups

This paper describes a simulation study of decision-making. It is based on a model of social influence in small, task-oriented, groups. A process model of dyadic social influence is built on top of a dynamic model of status and task participation that describes the emergence of a stable power and prestige order. Two models of group decision-making are examined: a static model for which the beliefs of actors do not change, and a process model for which they do as a function of the standing of each member of each interacting pair in the evolving power and prestige order. The models are compared on a set of N=111 cases, each requiring an affirmative or negative group response to a proposition A(c) that pertains to a case c. Initial beliefs are assigned to each of five members of distinct professions based on an analysis of independently collected behavioral data pertinent to the proposition to be affirmed or denied in each case. Although the two influence models yield identical decisions in 70% of the cases examined, the differences between them are statistically significant and in several instances show a medium effect size. Most importantly, the differences can be explained in terms of social influence and the status and task participation model on which it depends.Social Influence; Decision Processes; Social Networks; Group Dynamics; Simulation; Agent-Based Modeling

A game-theoretic approach to the socialization of utility-based agents

This paper presents a formal framework in which to study the socialization processes evolving among utility-based agents. These agents are self-interested, being their different social attitudes (cooperativeness, competitiveness or indifference) a consequence of this behavior. The dynamics of the socialization process are captured by a relation that measures the similarities between the desires of two groups of agents. This similitude relation is derived from the system's model, defined as a probabilistic transition system and a set of individual preference relations. Game-theoretic concepts are used in order to determine the rational(or expected) transitions of the system.(undefined

Dynamic clustering of evolving networks: some results on the line

International audienceUnderstanding the dynamics of evolving social/infrastructure networks is a central challenge in many applied areas such as epidemiology, viral marketing, city planification, etc. During the last decade, a massive amount of data has been collected on such networks that still resist to analysis. In this article, we propose to use the data on the dynamics to find better partitions of the network into groups by requiring the groups to be stable over time. For that purpose, we introduce a dynamic version of the k-clustering problem which includes a cost for every point that moves from one cluster to another. We show that this yields in many realistic situations better fitting solutions than optimizing independently various snapshots of the network. We present a first non-trivial exact algorithm for this problem when the points move along a line; this algorithm runs in polynomial time when k and the time horizon are bounded by a constant. We conclude with a series of surprising results on the complexity of the structure of optimal solutions for the line case

Self-Actualization through Conscientization

This article takes a critical look at how Theatre of the Oppressed is assisting the self and social transformation of severely disadvantaged groups that fall into the legal and political gaps. Specifically, it will look at the ideological essence of Freire’s conscientization, as prompted through Theatre of the Oppressed workshops run with asylum seekers in Melbourne. It will focus on the early stages of the conscientization process which centers on the notion of ‘self’ through reflection and contextual orientation. This will encompass an analysis into the old, new and evolving definitions of ‘oppressed’ and oppressive dynamics with relation to Theatre of the Oppressed poetics. Discussion will then move beyond this notion of recognition of the oppressed self to verbalization as an acknowledgement of oppression. Later it discusses workshops and group dynamics as conscientizing elements that promote transformation of the self

Homophily, Cultural Drift and the Co-Evolution of Cultural Groups

In studies of cultural differentiation, the joint mechanisms of homophily and influence have been able to explain how distinct cultural groups can form. While these mechanisms normally lead to cultural convergence, increased levels of heterogeneity can allow them to produce global diversity. However, this emergent cultural diversity has proven to be unstable in the face of "cultural drift"- small errors or innovations that allow cultures to change from within. We develop a model of cultural differentiation that combines the traditional mechanisms of homophily and influence with a third mechanism of 2network homophily", in which network structure co-evolves with cultural interaction. We show that if social ties are allowed to change with cultural influence, a complex relationship between heterogeneity and cultural diversity is revealed, in which increased heterogeneity can reduce cultural group formation while simultaneously increasing social connectedness. Our results show that in certain regions of the parameter space these co-evolutionary dynamics can lead to patterns of cultural diversity that are stable in the presence of cultural drift.Comment: (8 pages, 8 figures