Tootfinder

This https://arxiv.org/abs/2501.07327 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csSI_…

Community Aware Temporal Network Generation
The advantages of temporal networks in capturing complex dynamics, such as diffusion and contagion, has led to breakthroughs in real world systems across numerous fields. In the case of human behavior, face-to-face interaction networks enable us to understand the dynamics of how communities emerge and evolve in time through the interactions, which is crucial in fields like epidemics, sociological studies and urban science. However, state-of-the-art datasets suffer from a number of drawbacks, su…

This https://arxiv.org/abs/2409.10289 has been replaced.
link: https://scholar.google.com/scholar?q=a

ReflectDiffu:Reflect between Emotion-intent Contagion and Mimicry for Empathetic Response Generation via a RL-Diffusion Framework
Empathetic response generation necessitates the integration of emotional and intentional dynamics to foster meaningful interactions. Existing research either neglects the intricate interplay between emotion and intent, leading to suboptimal controllability of empathy, or resorts to large language models (LLMs), which incur significant computational overhead. In this paper, we introduce ReflectDiffu, a lightweight and comprehensive framework for empathetic response generation. This framework inc…

Defining and classifying models of groups: The social ontology of higher-order networks
Jonathan St-Onge, Randall Harp, Giulio Burgio, Timothy M. Waring, Juniper Lovato, Laurent H\'ebert-Dufresne
https://arxiv.org/abs/2507.02758

Defining and classifying models of groups: The social ontology of higher-order networks
In complex systems research, the study of higher-order interactions has exploded in recent years. Researchers have formalized various types of group interactions, such as public goods games, biological contagion, and information broadcasting, showing how higher-order networks can capture group effects more directly than pairwise models. However, equating hyperedges-edges involving more than two agents-with groups can be misleading, as it obscures the polysemous nature of ``group interactions''.…

Increasing Efficiency of the Chain of Contagion Task
Lars OM Rothkegel, Jakob Fink-Lamotte
https://arxiv.org/abs/2506.19314 https://a…

Increasing Efficiency of the Chain of Contagion Task
The chain of contagion task (CCT) is a pychological test to measure the amount of contagious beliefs in individuals. Contagious beliefs thereby refer to the perception that certain objects, people, or substances can transmit contamination through mere contact or proximity (Rozin et al., 1986). In the CCT, a neutral object (usually a pen) is rubbed against an inherently disgusting object (e.g. a toilet paper with feces) and participants are asked how contaminated this pen is on a scale from 0 (n…

A Compartmental Model for Epidemiology with Human Behavior and Stochastic Effects
Christian Parkinson, Weinan Wang
https://arxiv.org/abs/2507.01046 https:/…

A Compartmental Model for Epidemiology with Human Behavior and Stochastic Effects
We propose a compartmental model for epidemiology wherein the population is split into groups with either comply or refuse to comply with protocols designed to slow the spread of a disease. Parallel to the disease spread, we assume that noncompliance with protocols spreads as a social contagion. We begin by deriving the reproductive ratio for a deterministic version of the model, and use this to fully characterize the local stability of disease free equilibrium points. We then append the determ…

Modification of a Numerical Method Using FIR Filters in a Time-dependent SIR Model for COVID-19
Felipe Rog\'erio Pimentel, Rafael Gustavo Alves
https://arxiv.org/abs/2506.21739

Modification of a Numerical Method Using FIR Filters in a Time-dependent SIR Model for COVID-19
Authors Yi-Cheng Chen, Ping-En Lu, Cheng-Shang Chang, and Tzu-Hsuan Liu use the Finite Impulse Response (FIR) linear system filtering method to track and predict the number of people infected and recovered from COVID-19, in a pandemic context in which there was still no vaccine and the only way to avoid contagion was isolation. To estimate the coefficients of these FIR filters, Chen et al. used machine learning methods through a classical optimization problem with regularization (ridge regressi…

Adaptive network dynamics and behavioral contagion in multi-state drug use propagation
Hsuan-Wei Lee, Yi-Hsuan Huang, Nishant Malik
https://arxiv.org/abs/2506.21766

Adaptive network dynamics and behavioral contagion in multi-state drug use propagation
Addictive behavior spreads through social networks via feedback among choice, peer pressure, and shifting ties, a process that eludes standard epidemic models. We present a comprehensive multi-state network model that integrates utility-based behavioral transitions with adaptive network rewiring, capturing the co-evolutionary dynamics between drug use patterns and social structure. Our framework distinguishes four distinct individual states by combining drug use behavior with addiction status, …

This https://arxiv.org/abs/2307.10800 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_mat…

Contagious McKean--Vlasov problems with common noise: from smooth to singular feedback through hitting times
We consider a family of McKean--Vlasov equations arising as the large particle limit of a system of interacting particles on the positive half-line with common noise and feedback. Such systems are motivated by structural models for systemic risk with contagion. This contagious interaction is such that when a particle hits zero, the impact is to move all the others toward the origin through a kernel which smooths the impact over time. We study a rescaling of the impact kernel under which it conv…

This https://arxiv.org/abs/2309.15511 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_qfi…

Measuring risk contagion in financial networks with CoVaR
The stability of a complex financial system may be assessed by measuring risk contagion between various financial institutions with relatively high exposure. We consider a financial network model using a bipartite graph of financial institutions (e.g., banks, investment companies, insurance firms) on one side and financial assets on the other. Following empirical evidence, returns from such risky assets are modeled by heavy-tailed distributions, whereas their joint dependence is characterized b…

Effects of higher-order interactions and homophily on information access inequality
Moritz Laber, Samantha Dies, Joseph Ehlert, Brennan Klein, Tina Eliassi-Rad
https://arxiv.org/abs/2506.00156

Effects of higher-order interactions and homophily on information access inequality
The spread of information through socio-technical systems determines which individuals are the first to gain access to opportunities and insights. Yet, the pathways through which information flows can be skewed, leading to systematic differences in access across social groups. These inequalities remain poorly characterized in settings involving nonlinear social contagion and higher-order interactions that exhibit homophily. We introduce a enerative model for hypergraphs with hyperedge homophily…

Generative Intelligence Systems in the Flow of Group Emotions
Fernando Koch, Jessica Nahulan, Jeremy Fox, Martin Keen
https://arxiv.org/abs/2507.11831 http…

Generative Intelligence Systems in the Flow of Group Emotions
Emotional cues frequently arise and shape group dynamics in interactive settings where multiple humans and artificial agents communicate through shared digital channels. While artificial agents lack intrinsic emotional states, they can simulate affective behavior using synthetic modalities such as text or speech. This work introduces a model for orchestrating emotion contagion, enabling agents to detect emotional signals, infer group mood patterns, and generate targeted emotional responses. The…