Long term analysis of social structure: evidence of age-based consistent associations in Alpine ibex

ABSTRACTDespite its recognized importance for understanding the evolution of animal sociality as well as for conservation, long term analysis of social networks of animal populations is still relatively uncommon. We investigated social network dynamics in males of a gregarious mountain ungulate (Alpine ibex, Capra ibex) over ten years focusing on groups, sub-groups and individuals, exploring the dynamics of sociality over different scales. Despite the social structure changing between seasons, the Alpine ibex population was highly cohesive: fission-fusion dynamics lead almost every male in the population to associate with each other male at least once. Nevertheless, we found that male Alpine ibex showed preferential associations that were maintained across seasons and years. Age seemed to be the most important factor driving preferential associations while other characteristics, such as social status, appeared less crucial. We also found that centrality measures were influenced by age and were also related to individual physical condition. The multi-scale and long-term frame of our study helped us show that ecological constrains, such as resource availability, may play a role in shaping associations in a gregarious species, but they cannot solely explain sociality and preferential association that are likely also to be driven by life-history linked physiological and social needs. Our results highlight the importance of long-term studies based on individually recognizable subjects to help us build on our understanding of the evolution of animal sociality.

Using Flies to Understand Social Networks

Many animals live in groups and interact with each other, creating an organized collective structure. Social network analysis (SNA) is a statistical tool that aids in revealing and understanding the organized patterns of shared social connections between individuals in groups. Surprisingly, the application of SNA revealed that Drosophila melanogaster, previously considered a solitary organism, displays group dynamics and that the structure of group life is inherited. Although the number of studies investigating Drosophila social networks is currently limited, they address a wide array of questions that have only begun to capture the details of group level behavior in this insect. Here, we aim to review these studies, comparing their respective scopes and the methods used, to draw parallels between them and the broader body of knowledge available. For example, we highlight how despite methodological differences, there are similarities across studies investigating the effects of social isolation on social network dynamics. Finally, this review aims to generate hypotheses and predictions that inspire future research in the emerging field of Drosophila social networks.

Credit Behaviors of Rural Households in the Perspective of Complex Social Networks

With the increasing number of social networks emerging and evolving, the influence of social networks on human behavior is now again a subject of discussion in academe. Dynamics in social networks, such as opinion formation and information sharing, are restricting or proliferating members’ behavior on social networks, while new social network dynamics are created by interpersonal contacts and interactions. Based on this and against the backdrop of unfavourable rural credit development, this article uses CHFS data to discuss the whole and heterogeneous impact of social networks on rural household credit behavior. The results show that (1) social networks can effectively promote rural household credit behavior; (2) social networks have a significant positive impact on both formal credit and informal credit, but the influence of the latter is stronger; (3) both emotional networks and instrumental networks have a positive impact on formal credit and informal credit, and their influences are stronger on informal credit; (4) the influence of emotional network is stronger than instrumental networks on either formal credit or informal credit.

The effect of exposure to digital appeals to participate in collective action posted by influentials on protest information sharing: Evidence from Japan and South Korea

Contemporary collective action theories put large horizontal digitally connected networks at the center of mass political action. They posit that information sharing among ordinary social media users makes possible new forms of rapid mass political action. However, recent research has shown that influential individuals can play a number of key roles in facilitating networked political action in seemingly leaderless movements. Still, the role of influential individuals in stimulating protest information sharing on social media is an important aspect of networked collective action that remains understudied. This study seeks to address this. Specifically, it investigates the following question: does exposure to appeals to engage in protest increase individuals’ motivation to share protest information? Drawing on evidence from an original survey experiment, this study shows that digital appeals to engage in collective action posted by influential individuals do elicit an increase in motivation to share the appeal. However, this result obtains only for Korean respondents, whereas influential appeals appear to have no effect on Japanese respondents. I argue that this difference is in part a function of different citizenship norms in the two countries, and the corresponding effects on social network dynamics. Preliminary analysis supports this interpretation, but further investigation is warranted.

Ideology, communication and polarization

Ideologically committed minds form the basis of political polarization, but ideologically guided communication can further entrench and exacerbate polarization depending on the structures of ideologies and social network dynamics on which cognition and communication operate. Combining a well-established connectionist model of cognition and a well-validated computational model of social influence dynamics on social networks, we develop a new model of ideological cognition and communication on dynamic social networks and explore its implications for ideological political discourse. In particular, we explicitly model ideologically filtered interpretation of social information, ideological commitment to initial opinion, and communication on dynamically evolving social networks, and examine how these factors combine to generate ideologically divergent and polarized political discourse. The results show that ideological interpretation and commitment tend towards polarized discourse. Nonetheless, communication and social network dynamics accelerate and amplify polarization. Furthermore, when agents sever social ties with those that disagree with them (i.e. structure their social networks by homophily), even non-ideological agents may form an echo chamber and form a cluster of opinions that resemble an ideological group. This article is part of the theme issue ‘The political brain: neurocognitive and computational mechanisms’.

Learning Automata-based Misinformation Mitigation via Hawkes Processes

Mitigating misinformation on social media is an unresolved challenge, particularly because of the complexity of information dissemination. To this end, Multivariate Hawkes Processes (MHP) have become a fundamental tool because they model social network dynamics, which facilitates execution and evaluation of mitigation policies. In this paper, we propose a novel light-weight intervention-based misinformation mitigation framework using decentralized Learning Automata (LA) to control the MHP. Each automaton is associated with a single user and learns to what degree that user should be involved in the mitigation strategy by interacting with a corresponding MHP, and performing a joint random walk over the state space. We use three Twitter datasets to evaluate our approach, one of them being a new COVID-19 dataset provided in this paper. Our approach shows fast convergence and increased valid information exposure. These results persisted independently of network structure, including networks with central nodes, where the latter could be the root of misinformation. Further, the LA obtained these results in a decentralized manner, facilitating distributed deployment in real-life scenarios.

Psychology of Transnational Terrorism and Extreme Political Conflict

Fear of transnational terrorism, along with a revitalization of sectarian nationalism, is sundering social and political consensus across the world. Can psychology help? The focus of this review is on the psychological and related social factors that instigate and sustain violent extremism and polarizing group conflict. I first describe the changing global landscape of transnational terrorism, encompassing mainly violent Islamist revivalism and resurgent racial and ethnic supremacism. Next, I explore the psychosocial nature of the devoted actor and rational actor frameworks, focusing on how sacred values, identity fusion, and social network dynamics motivate and maintain extreme violence. The psychology of the will to fight and die is illustrated in behavioral and brain studies with frontline combatants in Iraq, militant supporters in Morocco, and radicalizing populations in Spain. This is followed by a consideration of how to deal with value-driven conflicts and a discussion of how the Internet and social media encourage the propagation of polarized conflict.