arXiv subjects

Noa Pinter-Wollman

Publications and source records attributed to Noa Pinter-Wollman.

3 recordsLinked to original sources

arXiv2021

A guide to choosing and implementing reference models for social network analysis

Analyzing social networks is challenging. Key features of relational data require the use of non-standard statistical methods such as developing system-specific null, or reference, models that randomize one or more components of the observed data. Here we review a variety of randomization procedures that generate reference models for social network analysis. Reference models provide an expectation for hypothesis-testing when analyzing network data. We outline the key stages in producing an effective reference model and detail four approaches for generating reference distributions: permutation, resampling, sampling from a distribution, and generative models. We highlight when each type of approach would be appropriate and note potential pitfalls for researchers to avoid. Throughout, we illustrate our points with examples from a simulated social system. Our aim is to provide social network researchers with a deeper understanding of analytical approaches to enhance their confidence when tailoring reference models to specific research questions.

cs.SI↗

arXiv2018

The use of multilayer network analysis in animal behaviour

Network analysis has driven key developments in research on animal behaviour by providing quantitative methods to study the social structures of animal groups and populations. A recent formalism, known as \emph{multilayer network analysis}, has advanced the study of multifaceted networked systems in many disciplines. It offers novel ways to study and quantify animal behaviour as connected 'layers' of interactions. In this article, we review common questions in animal behaviour that can be studied using a multilayer approach, and we link these questions to specific analyses. We outline the types of behavioural data and questions that may be suitable to study using multilayer network analysis. We detail several multilayer methods, which can provide new insights into questions about animal sociality at individual, group, population, and evolutionary levels of organisation. We give examples for how to implement multilayer methods to demonstrate how taking a multilayer approach can alter inferences about social structure and the positions of individuals within such a structure. Finally, we discuss caveats to undertaking multilayer network analysis in the study of animal social networks, and we call attention to methodological challenges for the application of these approaches. Our aim is to instigate the study of new questions about animal sociality using the new toolbox of multilayer network analysis.

q-bio.PE↗

arXiv2017

Task allocation and site fidelity jointly influence foraging regulation in honey bee colonies

Variation in behavior among group members often impacts collective outcomes. Individuals may vary both in the task that they perform and in the persistence with which they perform each task. Although both the distribution of individuals among tasks and differences among individuals in behavioral persistence can each impact collective behavior, we do not know if and how they jointly affect collective outcomes. Here we use a detailed computational model to examine the joint impact of colony-level distribution among tasks and behavioral persistence of individuals, specifically their fidelity to particular resource sites, on the collective tradeoff between exploring for new resources and exploiting familiar ones. We developed an agent-based model of foraging honey bees, parameterized by data from 5 colonies, in which we simulated scouts, who search the environment for new resources, and individuals who are recruited by the scouts to the newly found resources, i.e., recruits. We found that for each value of persistence there is a different optimal ratio of scouts to recruits that maximizes resource collection by the colony. Furthermore, changes to the persistence of scouts induced opposite effects from changes to the persistence of recruits on the collective foraging of the colony. The proportion of scouts that resulted in the most resources collected by the colony decreased as the persistence of recruits increased. However, this optimal proportion of scouts increased as the persistence of scouts increased. Thus, behavioral persistence and task participation can interact to impact a colony's collective behavior in orthogonal directions. Our work provides new insights and generates new hypotheses into how variation in behavior at both the individual and colony levels jointly impact the trade-off between exploring for new resources and exploiting familiar ones.

q-bio.PE↗