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ABSTRACT Communication and sociality are intimately related, as many important social processes are mediated by communication between signal senders and receivers. Despite recent advances in social network analysis, animal communication networks remain difficult to characterize because the interactions that comprise the network structure depend on receiver sensory, perceptual, and cognitive processes. Collectively, these receiver psychological traits process social information and lead to decisions regarding whether and how to interact with signallers, generating variation in social interactions and the structure of communication networks. Here, we review the evidence that variation in receiver psychology affects both individuals’ positions within the communication network and the structure of the communication network as a whole. These effects range from limits on signal active space imposed by receiver sensory acuity and sensitivity, to facilitation of social connections by learning and memory of signal characteristics. Although we identify numerous receiver psychological traits that likely affect connections between receivers and signallers, few studies have explicitly examined the role of receiver psychology on variation in communication network structure. We therefore review recent methodological advances that could facilitate such studies. We then show that the effects of receiver psychology on communication networks could have strong impacts on ecological and evolutionary processes. In particular, we discuss the reciprocal links between receiver psychology and social structure, and how these individual–group feedbacks are expected to generate coevolution between communication and sociality. Our review synthesizes diverse evidence that receiver psychology can affect communication interactions and provides a path forward for integrating sensory, perceptual, and cognitive mechanisms of signal processing with individual behavioural variation and ecological and evolutionary consequences of variation in animal social behaviour.
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Effects of network topology and trait distribution on collective decision making
Individual-level interactions shape societal or economic processes, such as infectious diseases spreading, stock prices fluctuating and public opinion shifting. Understanding how the interaction of different individuals affects collective outcomes is more important than ever, as the internet and social media develop. Social networks representing individuals' influence relations play a key role in understanding the connections between individual-level interactions and societal or economic outcomes. Recent research has revealed how the topology of a social network affects collective decision-making in a community. Furthermore, the traits of individuals that determine how they process received information for making decisions also change a community's collective decisions. In this work, we develop stochastic processes to generate networks of individuals with two simple traits: Being a conformist and being an anticonformist. We introduce a novel deterministic voter model for a trait-attributed network, where the individuals make binary choices following simple deterministic rules based on their traits. We show that the simple deterministic rules can drive unpredictable fluctuations of collective decisions which eventually become periodic. We study the effects of network topology and trait distribution on the first passage time for a sequence of collective decisions showing periodicity.
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- Award ID(s):
- 2054347
- PAR ID:
- 10433221
- Date Published:
- Journal Name:
- AIMS Mathematics
- Volume:
- 8
- Issue:
- 5
- ISSN:
- 2473-6988
- Page Range / eLocation ID:
- 12287 to 12320
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript
- Journal Article:
- https://doi.org/10.3934/math.2023619
