Hang-Hyun Jo

Bursty human dynamics

This book provides a comprehensive overview on emergent bursty patterns in the dynamics of human behaviour. It presents common and alternative understanding of the investigated phenomena, and points out open questions worthy of further investigations. n nThe book is structured as follows. In the introduction the authors discuss the motivation of the field, describe bursty phenomena in case of human behaviour, and relate it to other disciplines. The second chapter addresses the measures commonly used to characterise heterogeneous signals, bursty human dynamics, temporal paths, and correlated behaviour. These definitions are first introduced to set the basis for the discussion of the third chapter about the observations of bursty human patterns in the dynamics of individuals, dyadic interactions, and collective behaviour. The subsequent fourth chapter discusses the models of bursty human dynamics. Various mechanisms have been proposed about the source of the heterogeneities in human dynamics, which leads to the introduction of conceptually different modelling approaches. The authors address all of these perspectives objectively, highlight their strengths and shortcomings, and mention possible extensions to them. The fifth chapter addresses the effect of individual heterogeneous behaviour on collective dynamics. This question in particular has been investigated in various systems including spreading phenomena, random walks, and opinion formation dynamics. Here the main issues are whether burstiness speeds up or slows down the co-evolving processes, and how burstiness modifies time-dependent paths in the system that determine the spreading patterns of any kind of information or influence. Finally in the sixth chapter the authors end the review with a discussion and future perspectives. nIt is an ideal book for researchers and students who wish to enter the field of bursty human dynamics or want to expand their knowledge on such phenomena.

Dynamical Processes on Bursty Systems

In this chapter we will summarise the studies that address any type of dynamical processes on bursty human interaction networks. Bursty human interactions have indisputable consequences on dynamical processes, as their heterogeneous timings largely control the possible transmission of any kind of information between the interacting peers, or the timely connectedness of the temporal structure. To give a comprehensive review we first discuss all the possible bursty characters like the inter-event and residual time distributions, ordering of events, triggered event correlations, node and link burstiness, etc., which were shown to affect the early and late time behaviour of collective dynamical phenomena. In the second part of the chapter we go through all the main families of dynamical processes studied so far on bursty interaction networks to understand how process specific behaviour is dependent on the heterogeneous dynamics.

Models and Mechanisms of Bursty Behaviour

In this Chapter we will summarise the main modelling paradigms that have been used to get understanding of the emergence of bursty human behaviour. We address three main modelling paradigms concerning priority queuing models, reinforcement and memory driven processes, and Poisson models of bursty phenomena. In addition we also summarise less recognised modelling directions together with random reference models, which have been used lately to highlight the effects of burstiness and temporal correlations in empirical event sequences. We discuss several generative models at the individual level, where the activity dynamics of a single person were in focus, but we also summarise models of bursty dyadic interactions, and network models with emergent bursty behaviour.

Measures and Characterisations

In this Chapter we will present the theoretical description and characterisation of bursty human dynamics. Starting from the description of discrete time series we go through all the characteristic measures, like inter-event time distribution, burstiness parameter, memory coefficient, bursty train size distribution, autocorrelation function, etc., which were borrowed or introduced over the last decade to describe human bursty systems from the individual to the network level. With these quantities, we show how to detect the temporal inhomogeneities and long-range memory effects in the event sequences of human dynamics. At the same time we also introduce methods for system-level characterisation, mainly in the frame of temporal networks, that have been intensively studied in recent years to describe temporal human social behaviour. Finally, as human dynamics intrinsically show the cyclic patterns like daily and weekly ones, the methods for deciphering the effects of such cycles are also described.

Empirical Findings in Human Bursty Dynamics

In this Chapter we will present a comprehensive collection of a large number of empirical observations of human bursty behaviour in several datasets recorded in various situations. We divide these observations into two categories, i.e., individual activities and interaction-driven collective activities . In addition we also briefly discuss examples of human mobility , financial systems, and animal behaviour . Precisely, as for the interaction-driven case, we sort out the empirical findings from different social interaction modalities like face-to-face interactions , mobile-phone based interactions, communication by posted letters and emails to web-based social interactions, as they may reflect the different degree of sociality between a pair of individuals. To make the overview easier for a reader to follow such a large set of empirical studies, we present a systematic summary of all these observations in tables including a short description of each dataset, the observed values of some bursty characters, and the references to the original works.