On Universality in Human Correspondence Activity

Abstract

Identifying and modeling patterns of human activity has important ramifications in applications ranging from predicting disease spread to optimizing resource allocation. Because of its relevance and availability, written correspondence provides a powerful proxy for studying human activity. One school of thought is that human correspondence is driven by responses to received correspondence, a view that requires distinct response mechanism to explain e-mail and letter correspondence observations. Here, we demonstrate that, like e-mail correspondence, the letter correspondence patterns of 16 writers, performers, politicians, and scientists are well-described by the circadian cycle, task repetition and changing communication needs. We confirm the universality of these mechanisms by properly rescaling letter and e-mail correspondence statistics to reveal their underlying similarity.Power-law statistics are a hallmark of critical phenomena. A less obvious characteristic of crit-1

Temporal networks

“…regarding durations of time-respecting paths and latencies between vertices. Especially, for temporal networks of human communication, it has been discovered that such timings are often bursty and deviate from the more uniform times expected from a memoryless, random Poisson process [7,21,39,61,69,71,102,107,115,157,162]. Overall, the burstiness manifests itself in broader-than-expected distributions of inter-contact times, P(τ), defined either for nodes or their individual edges.…”

“…Importantly, there is an increasing body of evidence of very large heterogeneity in the timings of such interactions, from burstiness in patterns of communication via electronic and physical mail [7,39,61,69,115,157], mobile telephone calls and text messages [21,71,107,162], instant messaging [95], and patterns in proximity dynamics measured with RFID sensors [24,64,141]. Daily and circadian rhythms of human dynamics [58,67,94,102,103] may also play a role. Furthermore, there are correlations where interaction events trigger further events, such as reception of an email triggering a forwarding event, or incoming calls causing outgoing calls in mobile call networks [61,71,107,120].…”

“…Hence, although it destroys burstiness of events on individual vertices and edges as well as correlations between events such as triggered chains, the aggregated rate of events in the network is unchanged and will still follow the typical circadian and weekly patterns of human activity [58,67,94,102,103,170]. So far, results indicate [71] that such overall modulation of the event rate does not appear to matter at least for the simple SI spreading model, whose dynamics is dominated by edge burstiness (see Jo et al [67] for a method that removes the contribution of such circadian patterns).…”

Small but slow world: How network topology and burstiness slow down spreading

“…4. In order to exclude the possibility that the fat tail in the inter-event time distribution is only due to the broad weight distribution as suggested in [20], we calculated the distributions for binned weights and obtained a satisfactory scaling with the average inter-event time, similarly to [16]. We find that the distribution can be fitted by a power law with an exponent 0.7 over 3.5 decades, followed by a fast decay.…”

“…variation in overall communication frequency by the hour, is retained in every null model that is based on randomizing the original event sequence. In [20], it was suggested that natural periodicities, such as the daily cycle, are responsible for the fat-tailed waiting time distributions. In order to evaluate the impact of the daily pattern on the spreading speed, we carried out simulations where the aggregated MCN was used as the lattice.…”