Human Dynamics Research Papers - Academia.edu (original) (raw)

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- Human Dynamics, Amber, Bronze Age Amber Trade, Prehistoric amber

The butterfly effect is akin to the reality of economics. Chaos theory is big with economic ignorance.
This represents the dangers of ignorance in relation to the economic framework of our ecosystem. To deviate from this creates imbalances in the economic ecosystem. Because an efficient economic framework is rooted in natural law, life demands balance.

- by Nicholas A . Tartaglia
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- Business, Cognitive Psychology, Social Psychology, Economics
- by Myrna Mandell and +1
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- Public Administration, Political Science, Human Dynamics, Performance

Understanding Anasazi Culture Change Through Agent-Based Modeling Jeffrey S. Dean George J. Gumerman Joshua M. Epstein Robert L. Axtell Alan C. Swedlund Miles T. Parker Stephen McCarroll 1 INTRODUCTION Traditional narrative explanations... more

- by George Gumerman and +1
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- Human Dynamics, Cultural change, Computer Model, Agricultural Production

An agent-based computational model of Long House Valley, in northern Arizona near Monument Valley, is described and demontrated. The model, that runs from about AD 400 to 1400, consists of artificial adaptive agents (households) who inhabit a digitized version of the Long House Valley landscape. A detailed paleoenvironmental record exists for Long House Valley, based on alluvial geomorphology, palynology, and

- by Miles Parker
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- Human Dynamics, Cultural change, Computer Model, Agricultural Production

Long-standing results in urban studies have shown correlation of population and population density to a city’s pace of life,
empirically tested by examining whether individuals in bigger cities walk faster, spend less time buying stamps, or make greater
numbers of telephone calls. Contemporary social media presents a new opportunity to test these hypotheses. This study
examines whether users of the social media platform Twitter in larger and denser American cities tweet at a faster rate than
their counterparts in smaller and sparser ones. Contrary to how telephony usage and productivity scale superlinearly with city
population, the total volume of tweets in cities scales sublinearly. This is similar to the economies of scale in city infrastructures
like gas stations. When looking at individuals, however, greater population density is associated with faster tweeting. The
discrepancy between the ecological correlation and individual behavior is resolved by noting that larger cities have sublinear
growth in the number of active Twitter users. This suggests that there is a more concentrated core of more active users that
may serve an information broadcast function for larger cities, an emerging group of “town tweeters” as it were.

- by Dhiraj Murthy
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- Computational Sociology, Human Dynamics, Twitter, Urban Culture

The decisions animals make about how long to wait between activities can determine the success of diverse behaviours such as foraging, group formation or risk avoidance. Remarkably, for diverse animal species, including humans, spontaneous patterns of waiting times show random 'burstiness' that appears scale-invariant across a broad set of scales. However, a general theory linking this phenomenon across the animal kingdom currently lacks an ecological basis. Here, we demonstrate from tracking the activities of 15 sympatric predator species (cephalopods, sharks, skates and teleosts) under natural and controlled conditions that bursty waiting times are an intrinsic spontaneous behaviour well approximated by heavy-tailed (power-law) models over data ranges up to four orders of magnitude. Scaling exponents quantifying ratios of frequent short to rare very long waits are species-specific, being determined by traits such as foraging mode (active versus ambush predation), body size and prey preference. A stochastic-deterministic decision model reproduced the empirical waiting time scaling and species-specific exponents, indicating that apparently complex scaling can emerge from simple decisions. Results indicate temporal power-law scaling is a behavioural 'rule of thumb' that is tuned to species' ecological traits, implying a common pattern may have naturally evolved that optimizes move-wait decisions in less predictable natural environments.

- by Nicolas Humphries
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- Human Dynamics, Probability, Biological Sciences, Random Walk

This paper presents a data-driven agent-based simulation of individual mobility based on spatio-temporal data from mobile phones. The model developed is embedded within the CityScope framework, a platform used as decision support system for urban planning. This work analyzes the Andorra visitors’ flow and traffic congestion through an agent-based visualization using different representation and abstraction features.

- by Luis Alberto Alonso Pastor
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- Machine Learning, Data Analysis, Urban Planning, Human Dynamics

Darwinian studies of collective human behaviour, which deal fluently with change and are grounded in the details of social influence among individuals, have much to offer "social" models from the physical sciences which have elegant statistical regularities. Although Darwinian evolution is often associated with selection and adaptation, "neutral" models of drift are equally relevant. Building on established neutral models, we present a general, yet highly parsimonious, stochastic model, which generates an entire family of real-world, right-skew socioeconomic distributions, including exponential, winner-takeall, power law tails of varying exponents, and power laws across the whole data. The widely used Barabási and Albert (1999) Science 286: 509-512 "B-A" model of preferential attachment is a special case of this general model. In addition, the model produces the continuous turnover observed empirically within these distributions. Previous preferential attachment models have generated specific distributions with turnover using arbitrary add-on rules, but turnover is an inherent feature of our model. The model also replicates an intriguing new relationship, observed across a range of empirical studies, between the power law exponent and the proportion of data represented in the distribution.

- by Mike Batty
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- Human Dynamics, Cultural Evolution, Social Influence, Biological Sciences

The co-evolution of social relationships and individual behavior in time and space has important implications, but is poorly understood because of the difficulty of closely tracking the everyday life of a complete community. We offer evidence that relationships and behavior co-evolve in a student dormitory, based on monthly surveys and location tracking through resident cellular phones over a period of nine months. We demonstrate that a Markov jump process could capture the co-evolution in terms of the rates at which residents visit places and friends. Our co-evolution model will be useful in bridging sensor networks data and organizational dynamics theories, simulating different ways to shape behavior and relationships, and turning mobile phone data into data products.

- by Bruno Lepri
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- Stochastic Process, Multiagent Systems, Computational Modeling, Human Dynamics

Human mobility is differentiated by time scales. While the mechanism for long time scales has been studied, the underlying mechanism on the daily scale is still unrevealed. Here, we uncover the mechanism responsible for the daily mobility patterns by analysing the temporal and spatial trajectories of thousands of persons as individual networks. Using the concept of motifs from network theory, we find only 17 unique networks are present in daily mobility and they follow simple rules. These networks, called here motifs, are sufficient to capture up to 90 per cent of the population in surveys and mobile phone datasets for different countries. Each individual exhibits a characteristic motif, which seems to be stable over several months. Consequently, daily human mobility can be reproduced by an analytically tractable framework for Markov chains by modelling periods of high-frequency trips followed by periods of lower activity as the key ingredient.

- by Marta Gonzalez
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- Computer Science, Human Dynamics, Medicine, Multidisciplinary

Big Data is conceived as the powerful tool to exploit all the potential of the Internet of Things and the Smart Cities. Historically several of the human-related behaviours have been modelled with Poisson distribution, but a new dimension of understanding about the human behaviours is reached through all the gathered data in the emerging smart environment. This work analyses the data from the European Project SmartSantander. This work has correlated the traffic behaviour with respect to the temperature in the Santander City. This has been presented as the evolution of both flows present a similar behaviour. The traffic distribution, aggregated by temperature bins, follows up a Poisson distribution model. Thereby, allowing interpolate and predict complex behaviours based on simple measures such as the temperature. At the same time, this data presents a burst behaviour (human dynamics), when the data is analysed in sequence, instead of aggregated by temperature bins. Therefore, this work concludes that human-related behaviours can be described with both, Poisson and Human Dynamics distribution, depending on how the data is represented and aggregated.

- by D. Genoud
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- Computer Science, Data Analysis, Human Dynamics, Internet of Things

This paper presents a data-driven agent-based simulation of individual mobility based on spatio-temporal data from mobile phones. The model developed is embedded within the CityScope framework, a platform used as decision support system for urban planning. This work analyzes the Andorra visitors' flow and traffic congestion through an agent-based visualization using different representation and abstraction features.

- by Luis Alberto Alonso Pastor
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- Machine Learning, Data Analysis, Urban Planning, Human Dynamics

Quantitative understanding of human movement behaviors would provide helpful insights into the mechanisms of many socioeconomic phenomena. In this paper, we investigate hu- man mobility patterns through analyzing taxi-trace datasets collected from five metropoli- tan cities in two countries. We focus on three statistics for each dataset: the displacement of each occupied trip, the duration of each occupied trip, and the time interval between successive occupied trips by the same taxi (interevent time). The results indicate that the displacement distributions of human travel by taxi tend to follow exponential laws in two displacement ranges rather than power laws; the trip duration distributions can be approx- imated by log-normal distributions; the interevent time distributions can be well charac- terized by log-normal bodies followed by power law tails. For each considered measure, the rescaled distributions of all cities collapsed into a master curve. These results provide em- pirical evidence supporting the common regularity of intra-city human mobility. Moreover, we show that airport locations could play a role in explaining the spikes of displacement distributions of taxi trips in certain cities.

- by Lin Pan
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- Human Dynamics, Urban Computing, Human Mobility, Taxis