Institute for Complex Systems - Sapienza - CNR

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ISC Sapienza Human and Social Dynamics

Human and Social Dynamics

Rules and Exceptions in Language Dynamics

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In all languages, rules have exceptions in the form of irregularities. Since rules make a language efficient, the persistence of irregularity is an anomaly. How language systems become rule governed, how and why they sustain exceptions to rules? Frequent words are unlikely to change over time (e.g., frequent verbs tend to maintain an irregular past tense form). What is the role of frequency in maintaining exceptions to rules?

Last Updated on Tuesday, 03 November 2015 16:37 Read more...

Statistical physics modeling of social dynamics

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In recent years it has become widely recognized that many large-scale phenomena observed in social systems are the "macroscopic" complex effect of the "microscopic" simple behavior of a large number of interacting agents. This has led social scientists to the introduction of elementary models of social behavior (cellular automata, agent-based models). Many of these models are somehow relatives of models that have been introduced in modern traditional statistical physics, and it is natural to approach them using the same concepts and tools that have been successfully applied in physics. For a general introduction to these models and the approach of statistical physicists to them, see the review article

Last Updated on Monday, 17 November 2014 17:24 Read more...

Regularities and universality in large-scale social phenomena

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In social phenomena every individual interacts with a limited number of peers, usually negligible as compared with the total number of people in the system. In spite of that, human societies are characterized by stunning global regularities. There are transitions from disorder to order, like the spontaneous emergence of a common language/culture or the creation of consensus about a specific topic. In order to understand the nature and the origin of such regularities it is crucial to characterize them in a quantitatively precise way, looking in particular for features that are universal, i.e. shared by different phenomena. The identification of such features is fundamental for devising sensible simple models able to reproduce the empirical observations and suitable for theoretical investigation.

 

Last Updated on Tuesday, 05 February 2013 18:47 Read more...

Human Dynamics

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Until now, the study of human dynamics has been done only qualitatively. Actually, the present possibility to have quantitative data on the kind and nature of social relationships through social networks is driving a rapid change in the field. Thanks to the emergence of detailed datasets that capture human behavior, we can now follow specific human actions in ultimate detail. One of the first measurable quantity with which one can describe the relationship between humans is the timing and order with which we perform specific tasks. More specifically we want to know if it is possible to model the timing of a series of actions like receiving a phone call, sending an email, booking a flight etc. As in many other complex systems the traditional models have assumed so far that the timing of human actions is random. Some seminal papers by Barabasi and coauthor show that this is not the case. Rather the dynamics of many social, technological and economic phenomena are distributed along a fat tail distribution, that is to say the waiting time for a task to be executed follows a non-Poisson statistics, characterized by bursts of rapidly occurring events separated by long periods of inactivity. More interestingly it is simple to show that the bursty nature of human behaviour is a consequence of a decision-based queuing process: when individuals execute tasks based on some perceived priority, the timing of the tasks will be heavy tailed, with most tasks being rapidly executed, whereas a few experience very long waiting times. In contrast, random or priority blind execution is well approximated by uniform inter-event statistics.

Last Updated on Thursday, 03 March 2011 11:20 Read more...