Group-level Dynamics Research Articles

Emergence of group size disparity in growing networks with adoption

Social and technical networks undergo constant evolution driven by both existing entities and newcomers. In academia, research papers are continually cited by new papers, while senior researchers integrate newly arrived junior researchers into their academic networks. Moreover, social systems can be influenced by external factors that could indirectly impact their growth patterns. For instance, systematic discrimination against certain groups in academia or managerial positions can impede their long-term growth, especially when combined with group-level preferences in hiring or adoption, as observed in our study. To address this, we introduce a network growth and adoption model where generalised preferential attachment and asymmetric mixing act as the two fundamental mechanisms of growth and adoption. We show analytically and numerically that these mechanisms can recover the empirical properties of citation and collaboration growth, as well as the inequalities observed in the growth dynamics of groups. This model can be used to investigate the effect of intervention in group mixing preferences to overcome the cumulative disparities in the group-level dynamics.

Youth responses to state-manufactured diaspora mobilization: Turkey’s diaspora governance and the politics of selective engagement

ABSTRACT Turkey’s ruling Justice and Development Party (AKP) has implemented transnational policies to strengthen ties among diaspora youth in Europe with Turkey. However, these policies have been highly selective and geared towards regime-loyal groups in the diaspora. This article focuses on the group-level dynamics of AKP’s transnational youth outreach and examines the responses of dissident youth in the diaspora to these policies. We argue that there is significant variation in how AKP’s youth outreach strategies are received by diaspora youth and that the AKP’s state-sponsored intervention in diasporic spaces not only transforms loyalist diaspora organizations, but also affects the identification and mobilization dynamics of dissident groups.

A novel subject-wise dictionary learning approach using multi-subject fMRI spatial and temporal components

The conventional dictionary learning (DL) algorithms aim to adapt the dictionary/sparse code to individual functional magnetic resonance imaging (fMRI) data. Thus, lacking the capability to consolidate the spatiotemporal diversities offered by other subjects. Considering that subject-wise (sw) data matrix can be decomposed into the sparse linear combination of multi-subject (MS) time courses and MS spatial maps, two new algorithms, sw sequential DL (swsDL) and sw block DL (swbDL), have been proposed. They are based on the novel framework, defined by the mixing model, where base matrices prepared by operating a computationally fast sparse spatiotemporal blind source separation method over multiple subjects are employed to adapt the mixing matrices to sw training data. They solve the optimization models formulated using l_0/l_1-norm penalization/constraints through dictionary/sparse code pair update and alternating minimization approach. They are unique because no existing sparse DL method can incorporate MS spatiotemporal components while updating sw atoms/sparse codes, which can eventually be assembled using neuroscience knowledge to extract group-level dynamics. Various fMRI datasets are used to evaluate and compare the performance of the proposed algorithms with existing state-of-the-art algorithms. Specifically, overall, a 14% increase in the mean correlation value and 39% reduction in the mean computation time exhibited by swsDL and swbDL, respectively, over the adaptive consistent sequential dictionary algorithm.

Immune challenge changes social behavior in the guppy (Poecilia reticulata)

Abstract Increased exposure to pathogens is often considered to be one of the most significant costs of group living. As a result, animals typically avoid close association with individuals who manifest symptoms of disease. The question remains, however, whether avoidance behaviors are mediated by effects relating specifically to the disease itself, or through recognition of more general sickness behaviors that emerge from the activity of the immune system in response to infection. Here we examined the effects of an immune challenge, induced through exposure to bacterial lipopolysaccharides (LPS), on individual and social behavior in female guppies (Poecilia reticulata). We found that in a binary choice presentation, healthy focal individuals showed a strong preference to associate with stimulus shoals of saline-injected fish rather than stimulus shoals of LPS-injected fish. In a subsequent examination of group-level dynamics, shoals of LPS-injected females were more dispersed than similar shoals comprised of control fish and showed less coherent collective behavior despite the lack of any obvious difference in general activity between LPS and control fish. We discuss these findings in relation to the need for social animals to mitigate the risk of disease that is associated with living in proximity to conspecifics.

The State of the Art of Diagnostic Multiparty Eye Tracking in Synchronous Computer-Mediated Collaboration.

In recent years, innovative multiparty eye tracking setups have been introduced to synchronously capture eye movements of multiple individuals engaged in computer-mediated collaboration. Despite its great potential for studying cognitive processes within groups, the method was primarily used as an interactive tool to enable and evaluate shared gaze visualizations in remote interaction. We conducted a systematic literature review to provide a comprehensive overview of what to consider when using multiparty eye tracking as a diagnostic method in experiments and how to process the collected data to compute and analyze group-level metrics. By synthesizing our findings in an integrative conceptual framework, we identified fundamental requirements for a meaningful implementation. In addition, we derived several implications for future research, as multiparty eye tracking was mainly used to study the correlation between joint attention and task performance in dyadic interaction. We found multidimensional recurrence quantification analysis, a novel method to quantify group-level dynamics in physiological data, to be a promising procedure for addressing some of the highlighted research gaps. In particular, the computation method enables scholars to investigate more complex cognitive processes within larger groups, as it scales up to multiple data streams.

Alcohol use by Athletes: Hierarchy, status, and Reciprocity

Sport is considered a positive, health enhancing lifestyle choice. However, there is considerable evidence that many athletes, particularly those at university, engage in harmful levels of alcohol use. Despite decades of research showing student athletes consume alcohol at high levels, there have been no substantial in-roads into reducing consumption. At present, there is a need to better understand the social, cultural, and personal factors that drive athletes to consume harmful levels of alcohol. This study aimed to address this gap in literature by investigating the group level dynamics which may be driving heavy alcohol use and jeopardising attempts to reduce drinking. Over the course of one academic year, male (n = 9) and female (n = 6) rugby union athletes were recruited to take part in semi-structured interviews. Three overarching themes were identified that best represented the research findings, these were 1) social hierarchy, where alcohol use was used to create and sustain a social hierarchy, 2) status, where alcohol use was used to gain a reputation, and 3) reciprocity, where experienced athletes felt novices needed to go through the same (often painful and degrading) experiences they had. This study suggests that past approaches to reduce alcohol use among student athletes have substantially over-simplified the relationship and have over-focussed on the psychological contributors to this complex phenomena.

The Application of Continuous-Time Markov Chain Models in the Analysis of Choice Flume Experiments

Abstract An inhomogeneous continuous-time Markov chain model is proposed to quantify animal preference and avoidance behaviour in a choice experiment. We develop and apply our model to a choice flume experiment designed to assess the preference or avoidance responses of sea bass (Dicentrarchus labrax) exposed to chlorinated seawater. Due to observed fluctuations in chlorine levels, a stochastic process was applied to describe and account for uncertainty in chlorine concentrations. A hierarchical model was implemented to account for differences between eight experimental runs and use Bayesian methods to quantify preference/avoidance after accounting for observed shoaling behaviour. The application of our method not only overcomes the need to track individuals during an experiment but also circumvents temporal autocorrelation and any violations of independence. Our model therefore surpasses current methods in choice chamber studies, incorporating variability in the environment and group-level dynamics to yield results that scale and generalise to the real-world.

The consistency of individual centrality across time and networks in wild vervet monkeys.

Previous primate social network studies largely limited their focus to grooming and/or aggression networks, particularly among adult females. In addition, the consistency of individuals' network centrality across time and/or different networks has received little attention, despite this being critical for a global understanding of dynamic social structure. Here, we analyzed the grooming, aggression, and play social networks of a group of 26-28 wild vervet monkeys (Chlorocebus pygerythrus), including adults and juveniles, over two periods of 6 months. We collected data on grooming, play, and aggression using focal animal sampling with instantaneous recording and ad libitum sampling. We examined whether individuals' network centralities were consistent over the two periods and across networks, as well as the effect of age, sex, and dominance rank on three individual centrality metrics in each network and within each study period. We found that individuals were quite consistent in their network position from 1 year to the next despite changes in group composition. However, their network centralities were not correlated across networks, except for Strength and weighted Eigenvector centrality between grooming and aggression networks. We also found that in the aggression network, high-rankers showed the highest centrality in most network metrics (e.g., Degree, Strength, and Eigenvector centrality) and compared to males, females were most central in 2017 but not in 2018. In the grooming network, high-ranking females had the highest Eigenvector centrality, whereas in the play network, juvenile males had the highest Eigenvector centrality. Our findings corroborate previous findings on vervet monkeys. In addition, they show that individuals' network centralities may vary among networks and over time; thus highlighting the effect of sociodemographics and behaviors' functions on the group level dynamics of social behavior.

Locomotion and habituation to novel experimental environments in a social fish species

Abstract The response of animals to novel environments forms the basis of open field tests, an assay extensively used in the study of animal behaviour. However, to assess an animal’s routine behaviour or measure their response to novel environments, researchers must provide enough time for proper exploration and habituation. Unfortunately, no study has ever explicitly characterized the habituation process, except on isolated individuals, which represents an unusual situation for many social species. We analysed the movement characteristics and group-level dynamics of a shoaling fish species (Gambusia holbrooki) in an open-field arena for 1.5 h. We tested groups of 4 fish with varying sex ratios and found that behaviour changed over time with exploratory behaviour followed by a decreasing then plateauing trend, which only stabilised after 29 min. This movement pattern was consistent across all different sex ratios, however, female-skewed groups showed higher levels of activity during the first few minutes. Finally, median nearest neighbour distance was initially low before increasing and finally stabilising at around 9 min (with some exceptions) following the introduction of fish to the arena.

Decoding collective communications using information theory tools.

Organisms have evolved sensory mechanisms to extract pertinent information from their environment, enabling them to assess their situation and act accordingly. For social organisms travelling in groups, like the fish in a school or the birds in a flock, sharing information can further improve their situational awareness and reaction times. Data on the benefits and costs of social coordination, however, have largely allowed our understanding of why collective behaviours have evolved to outpace our mechanistic knowledge of how they arise. Recent studies have begun to correct this imbalance through fine-scale analyses of group movement data. One approach that has received renewed attention is the use of information theoretic (IT) tools like mutual information, transfer entropy and causation entropy, which can help identify causal interactions in the type of complex, dynamical patterns often on display when organisms act collectively. Yet, there is a communications gap between studies focused on the ecological constraints and solutions of collective action with those demonstrating the promise of IT tools in this arena. We attempt to bridge this divide through a series of ecologically motivated examples designed to illustrate the benefits and challenges of using IT tools to extract deeper insights into the interaction patterns governing group-level dynamics. We summarize some of the approaches taken thus far to circumvent existing challenges in this area and we conclude with an optimistic, yet cautionary perspective.

The impact of peer evaluation on team effort, productivity, motivation and performance in global virtual teams

PurposeThis study aims to assess the effect of peer evaluations on team-level effort, productivity, motivation and overall team performance.Design/methodology/approachThis study explores the impact of a peer evaluation system on 895 multicultural and transnational global virtual teams (GVTs) composed of 5,852 university students from 130 different countries. The study uses a quasi-experiment in which the group project is implemented under two conditions over two sequential iterations. In the first condition, team members do not receive peer evaluation feedback during the project. In the second condition, participants completed detailed peer evaluations of their team members and received feedback weekly for eight consecutive weeks.FindingsResults suggest that when peer evaluations are used in GVTs during the project, teams show: higher levels of group effort; lower levels of average productivity and motivation; and no clear evidence of improved team performance. Results cast doubts on the benefits of peer evaluation within GVTs as the practice fails to reach its main objective of improving team performance and generates some negative internal dynamics.Practical implicationsThe major implication of the study for managers and educators using GVTs is that the use of peer evaluations during the course of a project does not appear to improve objective team performance and reduces team motivation and perception of productivity despite increases in teams’ perceptions of effort and performance.Originality/valueThis study contributes to the scanty literature regarding the impact of peer evaluation systems on group-level dynamics and performance outcomes.

Integrating multi-level values and pro-environmental behavior in a U.S. protected area

Human behavior is influenced by an array of psychological processes such as environmental values. Despite the importance of understanding the reasons why people engage in activities that minimize environmental degradation, empirical research rarely integrates different types of values simultaneously to provide more complete and multi-faceted insights on how values contribute to environmental sustainability. Drawing from on-site survey data collected in Denali National Park and Preserve, Alaska (n = 641), we used two-step structural equation modeling to test how variation in behavioral patterns was explained by the cultural, individual, and social values of visitors to a national park. We fused various disciplinary perspectives on the value concept to demonstrate how individual- and group-level dynamics were integral for predicting behavior and better understanding aggregated preferences for environmental conditions in the context of a U.S. protected area.

The effects of prestige on collective performance and information flow in a strictly hierarchical institution

Institutions such as the military aim to respond efficiently to complex logistical challenges using a strictly hierarchical structure, where leaders are assigned a rank by senior colleagues and team members are trained to obey leader commands. Anthropologists have observed that leadership status outside of these top-down hierarchical institutions is often affected by the attribution of prestige by non-leaders. Here we show that even in the strictly hierarchical institutional context of the Royal Navy, informal prestige networks play a functional role in leadership efficacy and group-level dynamics. Specifically, a team leader’s informal prestige is a far stronger predictor of team performance and rate of information transmission during training exercises at sea than their formal rank. We find that the more decentralised the prestige network the more efficient it is for disseminating information. The implications of our findings for traditional conceptions of leadership in hierarchical institutions and the effects of prestige on group-level behaviour are discussed.

The Evolution of Tribalism: A Social-Ecological Model of Cooperation and Inter-Group Conflict Under Pastoralism

This study investigates a possible nexus between inter-group competition and intra-group cooperation, which may be called tribalism. Building upon previous studies demonstrating a relationship between the environment and social relations, the present research incorporates a social-ecological model as a mediating factor connecting both individuals and communities to the environment. Cyclical and non-cyclical fluctuation in a simple, two-resource ecology drive agents to adopt either go-it-alone or group-based survival strategies via evolutionary selection. Novelly, this simulation employs a multilevel selection model allowing group-level dynamics to exert downward selective pressures on individuals' propensity to cooperate within groups. Results suggest that cooperation and inter-group conflict are co-evolved in a triadic relationship with the environment. Resource scarcity increases inter-group competition, especially when resources are clustered as opposed to widely distributed. Moreover, the tactical advantage of cooperation in the securing of clustered resources enhanced selective pressure on cooperation, even if that implies increased individual mortality for the most altruistic warriors. Troubling, these results suggest that extreme weather, possibly as a result of climate change, could exacerbate conflict in sensitive, weather-dependent social-ecologies---especially places like the Horn of Africa where ecologically sensitive economic modalities overlap with high-levels of diversity and the wide-availability of small arms. As well, global development and foreign aid strategists should consider how plans may increase the value of particular locations where community resources are built or aid is distributed, potentially instigating tribal conflict. In sum, these factors, interacting with pre-existing social dynamics dynamics, may heighten inter-ethnic or tribal conflict in pluralistic but otherwise peaceful communities.

The leading role of the top management team in understanding family firms: Past research and future directions

Family firms are often lead by top management teams (upper echelons). Indeed, top management teams (TMTs) are a key determinant of the distinctiveness and heterogeneity of firms. Unfortunately, existing research on the role of the TMT in family firms remains fragmented. Using insights from upper echelons theory, this article systematically reviews and organizes the fragmented findings and arguments from prior research along three blocks: antecedents, processes, and outcomes of TMTs in family firms. In doing so, the article provides a summary of the current state-of-the-art of the literature and proposes a research agenda to open the TMT “black box” to examine TMT characteristics at the individual (demographics) and group level (dynamics and emotions) and determine their impact on family firm outcomes (entrepreneurial orientation, strategic choices, and performance) through future research efforts.

Cosmological and phenomenological transitions into how humans conceptualize and experience time

ABSTRACTCosmographies associated with Western cosmologies demonstrate transformations from classic wheels of time and chains of being to scales of nature, chronologies, and pedigrees. Pedigrees in turn are converted into linear timelines, bifurcating trees, and multidirectional networks. These diagrammatical transitions associate with changes in how time is conceptualized – as circular, linear, multilinear, multidirectional, and perhaps as non-existent. This paper focuses on delineating the phenomenologies associated with worldview turnovers. By identifying group-level dynamics, it demonstrates that time phenomenology extends individuals, and it demonstrates that paradigmatic shifts are driven by new observations, new jargon, and the invention of new quantitative methodologies and modelling techniques.

Socialization and violence

This article sets the stage for a special issue exploring group-level dynamics and their role in producing violence. My analytic focus is socialization, or the process through which actors adopt the norms and rules of a given community. I argue that it is key to understanding violence in many settings, including civil war, national militaries, post-conflict societies and urban gangs. While socialization theory has a long history in the social sciences, I do not simply pull it off the shelf, but instead rethink core features of it. Operating in a theory-building mode and drawing upon insights from other disciplines, I highlight its layered and multiple nature, the role of instrumental calculation in it and several relevant mechanisms – from persuasion, to organized rituals, to sexual violence, to violent display. Equally important, I theorize instances where socialization is resisted, as well as the (varying) staying power of norms and practices in an individual who leaves the group. Empirically, the special issue explores the link between socialization and violence in paramilitary patrols in Guatemala; vigilantes in the Bosnian civil war; gangs in post-conflict Nicaragua; rebel groups in the Democratic Republic of Congo, El Salvador, Sierra Leone and Uganda; post-conflict peacekeepers; and the US and Israeli military. By documenting this link, we contribute to an emerging research program on group dynamics and conflict.

Learning Scene-Independent Group Descriptors for Crowd Understanding

Groups are the primary entities that make up a crowd. Understanding group-level dynamics and properties is thus scientifically important and practically useful in a wide range of applications, especially for crowd understanding. In this paper, we show that fundamental group-level properties, such as intra-group stability and inter-group conflict, can be systematically quantified by visual descriptors. This is made possible through learning a novel collective transition prior, which leads to a robust approach for group segregation in public spaces. From the former, we further devise a rich set of group-property visual descriptors. These descriptors are scene-independent and can be effectively applied to public scenes with a variety of crowd densities and distributions. Extensive experiments on hundreds of public scene video clips demonstrate that such property descriptors are complementary to each other, scene-independent, and they convey critical information on physical states of a crowd. The proposed group-level descriptors show promising results and potentials in multiple applications, including crowd dynamic monitoring, crowd video classification, and crowd video retrieval.

Interactive Data Visualization for HIV Cohorts: Leveraging Data Exchange Standards to Share and Reuse Research Tools.

ObjectiveTo develop and disseminate tools for interactive visualization of HIV cohort data.Design and MethodsIf a picture is worth a thousand words, then an interactive video, composed of a long string of pictures, can produce an even richer presentation of HIV population dynamics. We developed an HIV cohort data visualization tool using open-source software (R statistical language). The tool requires that the data structure conform to the HIV Cohort Data Exchange Protocol (HICDEP), and our implementation utilized Caribbean, Central and South America network (CCASAnet) data.ResultsThis tool currently presents patient-level data in three classes of plots: (1) Longitudinal plots showing changes in measurements viewed alongside event probability curves allowing for simultaneous inspection of outcomes by relevant patient classes. (2) Bubble plots showing changes in indicators over time allowing for observation of group level dynamics. (3) Heat maps of levels of indicators changing over time allowing for observation of spatial-temporal dynamics. Examples of each class of plot are given using CCASAnet data investigating trends in CD4 count and AIDS at antiretroviral therapy (ART) initiation, CD4 trajectories after ART initiation, and mortality.ConclusionsWe invite researchers interested in this data visualization effort to use these tools and to suggest new classes of data visualization. We aim to contribute additional shareable tools in the spirit of open scientific collaboration and hope that these tools further the participation in open data standards like HICDEP by the HIV research community.

Strong personalities, not social niches, drive individual differences in social behaviours in sticklebacks

Understanding the mechanisms responsible for consistent individual differences in behaviour is a recent challenge for behavioural ecology. Although theory is rapidly developing in this area, there are few empirical tests. There are at least two hypotheses to explain why individuals behave differently from one another in a dynamic social environment. The social niche specialization hypothesis proposes that repeated social interactions generate consistent individual differences in social behaviour. The behavioural type hypothesis proposes that an individual's social behaviour reflects its behavioural type. We tested these two hypotheses by manipulating the opportunity for repeated social interactions in groups of three spine stickleback, Gasterosteus aculeatus, and by measuring the behavioural types of the same individuals in three contexts: when in a novel environment, when presented with an opportunity to associate with conspecifics and when confronted by an intruder. We found no evidence that repeated social interactions increased between-individual variation in social foraging behaviour. Instead, individuals' social foraging behaviour was related to their behavioural type, specifically their shoaling behaviour. In addition, the behavioural types of the members of a group strongly influenced a group's average foraging behaviour. Together, these results do not support the hypothesis that social dynamics within groups generates individual differences in behaviour. Instead, they suggest the reverse: individual differences in behaviour drive group-level dynamics.