European Institute for Statistics, Probability, Stochastic Operations Research and its Applications

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PROGRAMME

Wednesday May 18

Thursday May 19

Friday May 20

ABSTRACTS

Panos Argyrakis

Crisis spreading in world countries

We study the spreading of a crisis, such as the world crisis of the past few years and we model such events  by constructing a global economic network which uses financial information about the economic relationships between the different countries of the world. We then  spread this crisis from a single point of origin to the entire network by utilizing a the Susceptible-Infected-Recovered (SIR) epidemic model with a variable probability of infection. Each country can be infected by its neighbor country in the network with a certain probability. The probability of infection depends on the strength of economic relations between the pair of countries, and the strength of the target country, as it is natural for the economic dependence of one country  on its trading partners. The actual data that we use involve two different sets: (1) The import-export data for all countries of the world and (2) the number of subsidiaries that each private company has established in ot  her countries, by considering the 5000 largest world corporations. It is expected that a crisis which originates in a large country, such as the USA, has the potential to spread globally, such as the recent crisis that originated in the mortgage sector but spread practically in the entire banking industry. Surprisingly we show that in addition to the large economic powers in the world, countries with much lower GDP, such as Belgium, are also able to initiate a global crisis. Using the k-shell decomposition method to quantify the spreading power (of a node), we obtain a measure of ``centrality'' as a spreader of each country in the economic network. We thus rank the different countries according to the shell they belong to, and find the 12 most central countries. These countries are the most likely to spread a crisis globally. Of these 12 only six are large economies, while the other six are medium/small ones, a result that could not have been otherwise anticipated. Furthermo  re, we use our model to predict the crisis spreading potential of countries belonging to different shells according to the crisis magnitude. In comparing the results with the actual situation of the economies of all countries, we find a pretty good agreement between this new model and the extent of involvement of the crisis in each country. 

PRESENTATION

Marcel Ausloos

A generalized Verhulst approach of population evolution

Within Verhulst approach of population evolution, a discussion is presented taking into account that growth can neither be infinite nor reach a steady state at an inifinite asymptotic time. Some leveling-off should occur followed either by growth again or some decay. Examples are analyzed.

PRESENTATION

Vincent Buskens, Milena Tsvetkova

Egalitarian Networks from Asymmetric Relations: Coordination on Reciprocity in a Social Game of Hawk-Dove

Asymmetric relations such as lending money, doing favors and giving advice form the basis of mutual aid and cooperation in human societies. However, they also provide a mechanism for the emergence of inequalities and hierarchies. Reciprocal behavior at the dyadic and network levels can prevent the aggregation of unequal exchange into unfair macro-level outcomes. In this paper, we investigate the conditions under which a group of individuals is more likely to develop a social norm of reciprocity and coordinate on efficient and egalitarian structures from asymmetric dyadic relations. We present findings from a laboratory experiment on a version of the Hawk-Dove Game in which subjects interact repeatedly by choosing both their partners and actions towards each of them. Our results indicate that smaller groups are more likely to coordinate on egalitarian equilibria than larger groups and that norms of direct reciprocity are more likely to emerge than norms of indirect reciprocity. We also discover that although the equilibria are egalitarian in terms of payoffs, they imply a dominance hierarchy regarding the distribution of actions.

PRESENTATION

Carmen Costea

The fall of HR and the rise of excellence in human beings behavior

People, no matter their age, are more and more subject to intense learning processes often crowded with redundant or obsolete information, interspersed with challenging exams at all level. Unable sometimes to provide the appropriate information, teachers and Governments’ representatives are lost in inappropriate laws or agreements, long political talks because they have not the time to see the real benefit of training and education, they are not able to handle how to structure it, to monitor a project or to achieve the right goals.
Thus, educational inheritance remains simple remakes of undefined theoretical issues about the useless areas, disconnected from the real market potential and opportunities. Annually, the European Union spends huge funds with the main purpose to capacitate students learning towards excellence, to adapt ideas to their IQ and environment, to cooperate with their teachers as members of performing teams, to restructure the education from its fundaments. As lots of students choose their careers based on superficial or boomy reasons, their development goes along with fake responsibility; creativity is still understood as a copy-paste process; the funds release in dissonant consulting activity is more loss of time and money than motivation and real engagement. Upon graduation many adults become limited, unhappy, opportunistic careerists working hard to earn their bread and for whom their employment can not ever give the satisfaction of accomplishment. This is why most of reconversion programs fails and the funds are spent  without any achieved goals.
Often, the management theories, job ads, recruiting firms focus on qualities that can never be met by one person; they are looking for successful people, pro-active, intelligent individuals, sound professionals possessing inspirational leadership, good abilities to motivate teams, ability to work hard and under pressure, available after working time, handling several foreign, dynamic, competitive, etc.
This specialist portrait more likely fictional is increasingly rare in our new mercantile societies dominated by the small screen trends and models. Once the previous probation period gone they were replaced by short training periods under the European structural financement. During them, only a small number of newly hired staff is able to adapt to the company and job requirements as young learners for to find out the “secrets” of their chosen profession.
This is why we consider the need of a new paradigm in education, mainly in business education (BISOU) to fundamentally twist towards spiritual economy and human society. This is the single way to bring a new value system on which building appropriate models represent the challenge. The new approach is evolving as a dynamic, open system, related to ecological and social aspects of our days.
The educational variables that we analyze and interpret are linked to environmental and social variables of other systems related to the economic life. This requires a multidisciplinary and dynamic approach, integrating economic life ideas, with theories of ecology, sociology, political science, anthropology and psychology abilities proved as practical behavior. New economic science concepts about the health of the economy should be developed through inter-disciplinary pedagogy and research. The redefinition of a few basic economic and educational concepts in terms of the new paradigm would mean a real re-spiritualization and operational step toward identifying the value system that defines the new vision system.
Rethinking behavior in terms of new models cannot only remove their basic error - using money as the only variable to measure efficiency - but also introduce a new set of concepts and variables that are generated by the interaction with the ecological aspect of economy and society. It seems that measuring the efficiency of production processes in terms of net energy is more reliable than the macroeconomic analysis of monetary approaches. Such approach, initiated in Physics with Nicholas Georgescu Roegen work, tries out the entropic relevance of social systems life. The explanations of social friction dissipating unproductively the energy and resources become obvious and necessary at educational level to better support sound competition and reduce the conflicts.

PRESENTATION

Santo Fortunato

Characterizing and modeling online popularity

PRESENTATION

Koen Frenken
Coauthors: Luis R. Izquierdo, Paolo Zeppini

A branching and recombination model of innovationA branching and recombination model of innovation

To explain the dynamics of technological transitions, we develop an agent based model with network externalities and two different types of innovations. Recombinant innovations create short-cuts which speed up technological progress, allowing transitions that are impossible with only branching innovations. Our model replicates some stylized facts of technological transitions, such as punctuated equilibria, path dependency and technological lock-in. We find analytically a critical mass of innovators for successful innovations and technological transitions. Recombinant innovation counters network externalities, and calls for technological diversity as a key feature of technological transitions. An extensive simulation experiment shows that stronger network externalities are responsible for S-shaped utility and technological quality curves, indicating that a threshold of innovation probability is necessary to boost innovation. We finally introduce a policy view and interpret the innovation probability as the effort to foster technological change. A welfare measure including innovation costs presents an optimal interior value of innovation effort. The optimal innovation effort is strongly correlated with the number of recombinations, which further indicates how recombinant innovation is important in achieving a sustained technological progress at relatively low costs.

PRESENTATION

Serge Galam

Tailor Based Allocations for Multiple Authorship: a fractional gh-index

A quantitative modification to keep the number of published papers invariant under multiple authorship is suggested. In those cases, fractional allocations are attributed to each co-author with a summation equal to one. These allocations are tailored on the basis of each author contribution. It is denoted "Tailor Based Allocations (TBA)" for multiple authorship. Several protocols to TBA are suggested. The choice of a specific TBA may vary from one discipline to another. In addition, TBA is applied to the number of citations of a multiple author paper to have also this number conserved. Each author gets only a specific fraction of the total number of citations according to its fractional paper allocation. The equivalent of the h-index obtained by using TBA is denoted the gh-index. It yields values which differ drastically from those given by the h-index. The gh-index departs also from the one recently proposed by Hirsh to account for multiple authorship. Contrary to the h-index, the gh-index is a function of the total number of citations of each paper. A highly cited paper allows a better allocation for all co-authors while a less cited paper contributes essentially to one or two of the co-authors. The scheme produces a substantial redistribution of the ranking of scientists in terms of quantitative records. A few illustrations are provided.

David Goldberg

Connected Learning

This talk discusses a range of contemporary creative projects across digital humanities that  are computationally driven. The talk raises questions about the presumption of unidirectional contributions from the physical sciences, mathematics, and computation in solving humanistic problems and argues rather  for a more connected, collaborative, and interactive undertaking to address complex issues that are marked by irreducible technological, social, and cultural dimensions.

Vygintas Gontis
Coauthors:  Aleksejus Kononovičius and Bronislovas Kaulakys

Minimal agent based models as a microscopic reasoning of nonlinear stochastic models

Recently we introduced a double stochastic process driven by the nonlinear scaled stochastic differential equation reproducing the main statistical properties of the return, observed in the financial markets [1, 2]. The proposed model is based on the class of nonlinear stochastic differential equations, providing the power-law behavior of spectra and the power-law distributions of the probability density [3, 4]. Stochastic framework mainly gives only a macroscopic insight into the modeled system, while microscopic behavior currently is also of big interest. In this contribution we will provide a version of agent based herding model with transition to the nonlinear stochastic equations of trading activity and return in financial markets. We have modified Kirman’s ant colony agent based model [5] and introduced the trading activity as a measure of agent interaction frequency. This results in nonlinear stochastic differential equations for return adjustable to the expected statistical properties.

[1] V. Gontis, J. Ruseckas, A. Kononovičius, Long-range memory stochastic model of the return in financial markets, Physica A 389, 2010, p. 100 - 106, arXiv:0901.0903v3 [q-fin.ST]
[2] V. Gontis, J. Ruseckas, A. Kononovičius. A Non-Linear Double Stochastic Model of Return in Financial Markets, Stochastic Control, Chris Myers (Ed.), ISBN: 978-953-307-121-3, Sciyo, 2010, p. 559-580.
[3] B. Kaulakys, J. Ruseckas, V. Gontis, M.Alaburda, Nonlinear stochastic models of 1/f noise and powerlaw distributions, Physica A 365, 2006, p. 217-221, arXiv: cond-mat/0509626v1 [cond-mat.statmech].
[4] J. Ruseckas, B. Kaulakys, 1/f noise from nonlinear stochastic differential equations, Physical Review E 81, 2010, 031105, arXiv: 1002.4316v1 [nlin.AO]
[5] A. P. Kirman, Ants, rationality, and recruitment, Quarterly Journal of Economics 108, 1993, p. 137-156.

PRESENTATION

Igor Grabec, Franc Švegl

Forecasting development of traffic jam at a high-way bottleneck

Maintenance works on high-ways require installation of bottlenecks that cause instabilities of traffic flows and development of terrible jams. In order to provide for analysis of corresponding traffic instability and minimization of its influence, road operators have to forecast the properties of traffic jam in dependence of a planned bottleneck structure. The article presents an intelligent system that has been recently developed for this purpose. The system includes a non-parametric statistical model for forecasting of traffic flow rate on roads network in Slovenia and an analytical model for prediction of traffic jam evolution at a bottleneck. For this purpose a new fundamental diagram of traffic flow was developed that provides for accounting of bottleneck characteristics. Performance of the corresponding computer program is demonstrated using records of traffic flow rate at a point of maximal traffic activity on a high-way close to city Ljubljana.

PRESENTATION

Charles van den Heuvel, Richard Smiraglia

Idea Collider
Elementary knowledge structures in the humanities

The debate on atoms and voids in the universe (atomism) had an important impact on the emerging discipline of library science in the 19th century in which the universe of knowledge was a regular used metaphor. The use of this metaphor got a new impetus with the first formulations of the relativity and quantum theories. At the beginning of the 20th century classificationists such as the Belgian, Paul Otlet (1868-1944) visualized thought experiments in which knowledge contained in all sorts of documents was broken down into the tiniest elements and recombined in new knowledge structures. During the tests with the Large Hadron Collider in CERN in 2008, Richard Smiraglia (University of Wisconsin, Milwaukee) and Charles van den Heuvel set up a similar thought experiment to develop an Idea Collider that enables the identification of elementary structures of knowledge and its reconstruction along structural (syntactical) lines rather than with an semantic approach alone. In this paper I will discuss its potential for information retrieval in the humanities.

- Heuvel, C. van den, & Smiraglia, R.P. (2010). “Concepts as Particles: Metaphors for the Universe of Knowledge”,in Gnoli, C. and Mazzocchi, F. (Eds.), Paradigms and conceptual systems in knowledge organization: Proceedings of the Eleventh International ISKO Conference, 23-26 February 2010 Rome Italy, Ergon-Verlag, Würzburg, pp. 50-56.
- Smiraglia R. P.; Heuvel, Charles van den (2011), Idea Collider: From a theory of knowledge organization to a theory of knowledge interaction. Bulletin of the American Society of Information Science and Technology, April/May 37 (4), pp. 43-47
 

Jaroslav Hlinka

What can we learn from complex spatiotemporal dynamics of brain activity?

Human brain is an iconic example of a complex system. In recent decades, neuroimaging research has gathered an exponentially increasing wealth of data and results documenting its complex spatiotemporal behaviour. The motivations have stemmed from the impact our understanding of brain function and disease has on human well-being and socio-economical prosperity, but also from the deeply human fascination by the question of our identity.
Apart from strictly neuroscientific findings, the increasingly multidisciplinary area of brain research provides methodological and theoretical links to other fields of complex system study, fostering inter-disciplinary discussion and research. The presentation will give an overview of challenges regarding complex spatiotemporal properties of brain activity. Some of the highlighted features will include multi-scale temporal activity, with nested fast and slow oscillations and 1/f-type frequency distribution, and dynamic formation of functional networks based on a stable structural connectivity substrate.
However, the ultimate question is how a system of cooperating and/or competing (neural) populations can lead to an emergence of robust but highly flexible, effective and coordinated behaviour within a dynamic environment. We believe some of these questions, related to self-organization, are highly relevant for the whole field of complex systems.

Remco van der Hofstad

Shortest-weight problems on random graphs

We investigate shortest-weight problems on the configuration model, in which flow passes through the network minimizing the total weight along edges. In practice, one is both interested in the actual weight of the minimal weight path, which represents its cost, as well as the number of edges used or hopcount, as this is often a good measure of the delay observed in the network.
We assume that the edge weights, which represent the cost of using the edge in the network, are independent random variables.
We then investigate the total weight and hopcount of the minimal weight path. We study how the minimal weight and hopcount depend on the structure of the edge weights as well as on the structure of the graph. We present some recent results, as well as conjectures related to weak and strong disorder.
The above research is inspired by transport in real-world networks, such as the Internet. Measurements have shown fascinating features of the Internet, such as the `small world phenomenon'. The small world phenomenon states that typical distances in the network under consideration is small.
Also, the degrees in the Internet are rather different from the degree structure in classical random graphs. Internet is a key example of a complex network, other examples being the Internet Movie Data Base, social networks, biological networks, the WWW, etc.
Interestingly, many such complex networks share features with it. For example, the `six degrees of separation' paradigm states that social networks are small worlds, and many related complex networks are as well.
[This is joint work with Gerard Hooghiemstra, Shankar Bhamidi, Piet Van Mieghem, Henri van den Esker and Dmitri Znamenski.]

Yurij Holovatch

Collective behaviour in complex networks: scaling and beyond

In collaboration with C. von Ferber (Coventry/Freiburg), R. Folk (Linz), R. Kenna (Coventry), V. Palchykov (Lviv).

Phase transitions and critical behavior in complex networks currently attract much attention because of their unusual features and broad array of applications, ranging from socio- to nanophysics. The questions we address in this report concern two fundamental principles of critical phenomena: universality and scaling. Both of these questions have to be reconsidered when a system resides on a network. To this end, we consider several simple models  on scale-free networks and analyze their critical behavior in terms of scaling functions which are of fundamental interest in the theory of critical phenomena. We obtain general scaling functions for the equations of state and thermodynamical functions extending the principle of universality to systems on scale-free networks and quantifying an impact of fluctuations in the network structure on critical behavior. Moreover, we address the logarithmic corrections to the leading power laws governing thermodynamic quantities that appear as the second order phase transition point is approached. We show the validity of scaling relations for the new set of the logarithmic correction-to-scaling exponents and derive new scaling relations for the exponents of logarithmic corrections, for which these relations were unknown.
1. C. von Ferber, R. Folk, Yu. Holovatch, R. Kenna, V. Palchykov. Phys. Rev. E (2011), (to appear) [arXiv:1101.3680v1].
2. V. Palchykov, C. von Ferber, R. Folk, Yu. Holovatch, R. Kenna. Phys. Rev. E, vol. 82 (2010) 011145.

PRESENTATION

Janusz Holyst

CYBEREMOTIONS – Collective Emotions in Cyberspace

Emotions are an important part of most societal dynamics. As with face to face meetings, Internet exchanges may not only include factual information but also emotional information; how participants feel about the subject discussed or other group members. The development of automatic sentiment analysis has made possible a large scale emotion detection and analysis  using text messages collected from the web. Here results of two years studies performed in the frame of EU Project  CYBEREMOTIONS  (Collective Emotions  in Cyberspace) will be presented. The Project associates nearly 40 scientists from Austria, Germany, Great Britain, Poland, Slovenia and Switzerland.  The results include an automatic collection and classifying sentiment data in various e-communities, a qualitative and quantitative sentiment data analysis and data driven modeling of collective emotions by ABM, complex networks and fluctuation scaling paradigms, development of emotionally intelligent ICT to  ols such as affective dialog systems and graphically animated virtual agents that communicate by emotional interactions.
Emergence of collective emotions in cyber-communities will be demonstrated  by applying four different methods and using independent datasets that include several millions of records: (i) emotional avalanches distribution observed in BBC blogs, and Digg data; (ii) non-random emotional clusters distribution observed in Blogs06, BBC Forum, Digg and IRC channels; (iii) persistent character of sentiment dynamics observed  for IRC channels using the  Hurst exponent analysis; (iv) causal sentiment triad distribution found in Network Motives Analysis.

Stefan Hutzler

Analysis of online betting exchange data for the 2008 Champions League football tournament

(Stefan Hutzler, Stephen J. Hardiman and Peter Richmond(*) School of Physics, Trinity College Dublin, Ireland (*)Complex and Adaptive Systems Laboratory, University College Dublin, Ireland)

Online-betting has become increasingly popular. From our analysis of data for football matches traded at the betting exchange betfair.com, we find that as in financial markets, the probability distributions for the change in the market price (odds) are seen to exhibit fat tails [1]. Statistical differences exist between the returns that occur when the matches are under way (which we argue are driven by match events), and the returns that occur during half-time (which we ascribe to a trader-driven noise) [2].

[1] Hardiman SJ, Tobin ST, Richmond P and Hutzler S (2011), Distributions of certain market observables in an on-line betting exchange, Dynamics of Socio-Economic Systems, 2, 121-137.
[2] Hardiman SJ, Richmond P and Hutzler (2010), Long-range correlations in an online betting exchange for a football tournament, New Journal of Physics, 12, 105001.

Hans Kamermans

Predicting the Past for Present Purposes

Archaeological predictive modelling is a technique to predict, at a minimum, the location of archaeological sites or materials in a region, based either on the observed pattern in a sample or on assumptions about human behaviour.
Archaeologists use predictive modelling for two applications: to gain insight into former human behaviour in the landscape and to predict archaeological site location to guide future developments in the modern landscape. The last application is part of archaeological heritage management and has been heavily criticized by academic researchers. This presentation will summarize the critique, discuss the possibilities of predictive modelling and present some avenues for future research.

Bronislovas Kaulakys, Miglius Alaburda, Vygintas Gontis and Julius Ruseckas

The inverse cubic distributions from the point process model

The well-identified stylized fact is the so-called inverse cubic power-law of the cumulative distributions of a number of events of trades and of the logarithmic price change, which is relevant to the developed stock markets, to the commodity one, as well as to the most traded currency exchange rates [1-4].
A simple model, based on the point process model of 1/f noise [5], generating the long-range processes with the inverse cubic cumulative distribution is proposed and analyzed.
Main assumptions of the model are:
(i) the restricted additive Brownian motion in time of the inter-event interval for the frequent events (i.e., for small inter-event time τ) and
(ii) the multiplicative motion of the inter-event time τ(t) with the multiplicative noise proportional to the intensity of the process, 1/τ(t), for the large inter-event times [6].
It is shown that the additional Poissonian stochasticity of the events occurrence time does not influence the main conclusions of the model.
More complex equations for modeling the financial systems using the point process model and stochastic nonlinear differential equations have been introduced and analyzed in Refs. [7, 8].

1. P. Gopikrishnan, M. Meyer, L. A. N. Amaral and H. E. Stanley, Inverse cubic law for the distribution of stock price variations, Eur. Phys. J. B 3, 139 (1998).
2. X. Gabaix, P. Gopikrishnan, V. Plerou and H. E. Stanley, A theory of power-law distributions in financial market fluctuations, Nature (London), 423, 267 (2003).
3. R. K. Pan, S. Sinha, Inverse-cubic law of index fluctuation distribution in Indian markets, Physica A 387, 2055 (2008).
4. G.-H. Mu and W.-X. Zhou, Tests of nonuniversality of the stock return distributions in an emerging market, Phys. Rev. E 82, 066103 (2010).
5. B. Kaulakys, V. Gontis and M. Alaburda, Point process model of 1/f noise vs a sum of Lorentzians, Phys. Rev. E 71, 051105 (2005).
6. B. Kaulakys and M. Alaburda, Modeling the inverse cubic distributions by nonlinear stochastic differential equations, ICNF2011, Toronto, 12-16 June, 2011 (to be published).
7. V. Gontis and B. Kaulakys, Modeling long-range memory trading activity by stochastic differential equations, Physica A 382, 114 (2007).
8. V. Gontis, J. Ruseckas and A. Kononovicius, A long-range memory stochastic model of the return in financial markets, Physica A 389, 100 (2010).

PRESENTATION

Renaud Lambiotte

The Personality of Popular Facebook Users

Social science aims at understanding how large-scale behaviour emerges from the intrinsic properties of a large number of individuals and their pairwise interactions. Contrary to network connectivity, whose organization has been explored in email or mobile phone data, the psychological profile of large-scale populations has not been studied so far. In this work, we have analyzed data from a highly-popular Facebook application that is able to survey a very large number of Facebook users with peer-reviewed personality tests. Based on test results, we study the relationship between network importance (number of Facebook contacts) and personality traits, the first of its kind on a large number of subjects (400,000). We test to which extent two prevalent viewpoints hold. That is, sociometrically popular Facebook users (those with many social contacts) are the ones whose personality traits either predict many offline (real world) friends or  predict propensity to maintain  superficial relationships. We find that the strongest predictor for number of friends in the real world (Extraversion) is also the strongest predictor for number of Facebook contacts. We then verify a widely held conjecture that has been put forward by literary intellectuals and scientists alike but has not been tested: people who have many social contacts on Facebook are the ones who are able to adapt themselves to new forms of communication, present themselves in likable ways, and have propensity to maintain superficial relationships. We show that there is no statistical evidence to support such a conjecture.

Nelly Litvak

Correlations between power law parameters in complex networks

Correlations in complex networks play an important role in, for instance, robustness of the Internet, a range of an epidemic spread, and in information ranking. Yet, mathematical modelling and analysis of these correlations is a largely unresolved issue. In this talk we study the dependence between in-degree of a node and its ranking score computed by the celebrated Google PageRank algorithm. In a power law network, the PageRank ranking scores appear to follow a power law with the same exponent as in-degree. In this talk we characterize correlations between an in-degree and a PageRank score of a randomly chosen node. The dependencies between power law parameters can be evaluated using the so-called angular measure, a notion introduced in extreme value theory to describe the dependency between very large values of coordinates of a random vector. We use this theory to measure dependencies in Wikipedia, Web, and artificially constructed preferential attachment graphs. The results are strikingly different for the three samples. Next, for an analytical stochastic model, that captures correctly the PageRank power law behavior, we prove that the angular measure for in-degree and PageRank is concentrated in two points. This logically corresponds to the two main sources of high ranking: large in-degree and a high rank of one of the ancestors. However, capturing the correlations observed in real data, remains a challenging open problem.

PRESENTATION

Juergen Mimkes

The econophysics of autocracy and democracy in the Arab world

The thermodynamic formulation of social laws is based on the law of statistics under constraints, the Lagrange principle. This laws is called “free energy principle” in physics and has been applied successfully to all fields of natural science. In social sciences it may be applied to collective and individual behaviour of social, political or religious groups.
In homogeneous atomic systems we find the three states: solid, liquid, gas, depending on temperature and pressure. In homogeneous social systems we also find three states: collective, individual, global, depending on standard of living and social pressure. In homogeneous political systems we find again three states: autocratic, democratic, global, depending on standard of living and military pressure. For the 90 biggest countries in the world the transition from autocracy to democracy is in the range of 2.500 to 4.000 US $ per capita and a fertility rate below 3 children per woman. These parameters have been applied to the Arab world.

PRESENTATION

Erik Postma

Van Gogh's Uncertainty Principle

The presentation provides an overview of our attempts to identify forgeries by digitally analyzing van Gogh's paintings. In our approach, the joint uncertainty of location and spatial frequency, as addressed by Dennis Gabor in 1964, plays a central role.

Araceli N. Proto

Classical, Semiclassical and Quantum Models for Understanding Human Systems

The intense use of Information and Communications Technologies (ICT) into individuals life make that old problems (like socioeconomic uncertainty, labor stress, together with new problems as the digital divide and its consequent inequality, data protection, privacy, security, intellectual copyright ) emerge strongly, demanding the construction of new paradigms. Interaction among individuals, companies, governments, occurs great speed, not only between them but also among themselves. It is then necessary to develop tools for evaluation and prospecting of the complex dynamics of the IS in all involved areas : social, psychological, economical, productive, legal, ethical in a systematic way, in the understanding that the impact of the ICT in Society is irreversible and unavoidable. Up to this point it seems necessary to understand how individuals, collections of individuals, political and economical decisors behave considering that technological advances are faster th an the individuals psychological adaptation capacities (1). Pointing to the analysis of decision making processes, we describe some models coming from classical as well as quantum physics to provide a theoretical framework for at least some aspects of human behavior. The models are also suitable for mathematical psychology problems. We have been extensively studied these models, previously to apply them to human systems (2,3, and references therein).

1)J. R. Busemeyer , Z. Wang, J. T. Townsend, Quantum dynamics of human decision-making, Journal of Mathematical Psychology 50 (2006) 220-241.2)Decision making under stress: a Quantum Model approach, C.M. Sarris, A. N. Proto, Volume 2, Issue 2, 2010, Pages 359-373 ISSN - 0974-6811.3)Dynamic Peer-to-Peer Competition L.F. Caram, C.F. Caiafa, A.N. Proto and M. Ausloos, Physica A 389 (2010) 2628_2636, ISSN:0378-4371.

PRESENTATION

Milan Rajkovic

Statistical Mechanics of SImplicial Complexes: Spectral Entropy

In this exposition we focus on simplicial complexes (obtained from random, scale- free networks and networks with exponential connectivity distributions) and their persistent homological and cohomological properties. Simplicial complexes may be constructed from undirected or directed graphs (digraphs) in several different ways. Here we consider two of them: the neighborhood and the clique complex. We show how a new branch of statistical mechanics may be introduced which we call statistical mechanics of simplicial complexes. We also explore the topological properties of independent sets corresponding to each type of complex network, and their statistical features. Of special interest are the properties of eigenvalues and eigenfunctions of nonnormalized combiantorial Laplacian. Spectral entropy, obtained from the combinatorial Laplacian, reflects many new properties of a simplicial complex (complex network) and thus has important practical applications. We also derive a different type of entropy from a purely combinatorial aspect and explore its properties. In order to illustrate the advantages of simplicial complex approach over standard graph (networks) approach we present results of the analysis of several social type of networks.

Peter Richmond

House prices in London and Dublin revisited

A few years ago (2006) we analyzed data for house prices in both London and Dublin. An outcome of the analysis was that the then level of house prices would not be sustained and a fall in prices was imminent. How have prices fared since that time? How good was our prediction? In this presentation we review recent developments and update our analysis.

PRESENTATION

Giulia Rotundo

Complex principal component analysis of directed networks

A principal component analysis of a network implying two disinct communities is presented, in the line of studies on the structural properties of citation networks. The considered communities having markedly different opinions are the Neocreationist and Intelligent Design Proponents (IDP) on one hand, and the Darwinian Evolution Defenders (DED) on the other hand. The eigenvalues of the various whole, intra- and inter-community adjacency matrices are calculated before a Principal Component Analysis (PCA) is performed. The quotations of agents being intrinsically directed and not necessarily reciprocal, the adjacency matrices have complex eigenvalues, whence complex components of the eigenvectors. The PCA technique has thus to be generalized to the complex plane. As in standard cases, only two eigenvalues are selected for further discussion; those having the largest real parts. Polar plots of the corresponding eigenvector components are presented for initiating the discussion.

Stef Scagliola & Franciska de Jong

Enhanced Publication: e-humanities practices and multi-media data

The inevitable ‘digital turn’ in the Humanities has inspired many scholars in the Information Sciences to develop ICT-tools that can be applied in various phases of the research process: searching for data, processing data, sharing research results and presentation of them. Yet applying technological tools without the appropriate ‘mindset’ in which concepts such as data sharing, inter-subjectivity, open source and multi-disciplinarity have become common practice, can be problematic. This is certainly true in a realm where status and credits are inextricably connected to measurements of excellence in a competitive academic market. As a diligent apprentice of ICT-applications in the field of the Humanities, and inspired by what anthropologists term ‘participatory observation’ of the academic ‘tribe’,  I I would like to: 1. present some thoughts about the necessary preconditions to change old habits and ingrained conventions in the Humanities, with an emphasis on oral history/qualitative research, and,  2. illustrate my observations with an example of the application of ICT in qualitative research, the so called Enhanced Publication.

PRESENTATION
 

Andrea Scharnhorst

Evolution of the Wikipedia category structure

Wikipedia has a category feature, which is in place since 2004, where users were invited to tag (categorize) articles. Specific pages, so-called category pages, have been introduced. With help of them relations between regular articles as well as other category pages can be defined. As a result, we have two networks, the network between Wikipedia articles and the network between Wikipedia category pages. Both forming a directed network. In this paper, we analyze the evolution of the category system in terms of number of pages and number of links. We re-construct the category link network of Wikipedia at various time intervals and look into how this network and its properties evolve in time, especially during the rapid re-organizations.
(Suchecki, K.; Scharnhorst, A.; Akdag-Salah, A.; Gao, C.)

PRESENTATION

Ingve Simonsen

Persistent collective trend in stock markets

This talk presents empirical evidence for a significant difference in the collective trend of the share prices during the stock index rising and falling periods. Data on the Dow Jones Industrial Average and its stock components are studied between 1991 and 2008. Pearson-type correlations are computed between the stocks and averaged over stock-pairs and time. The results indicate a general trend: whenever the stock index is falling the stock prices are changing in a more correlated manner than in case the stock index is ascending. A thorough statistical analysis of the data shows that the observed difference is significant, suggesting a constant-fear factor among stockholders.

Sorin Solomon

Bosiljka Tadic

Emotions in Social Networks: Data Analysis and Agent-Based Modeling

Emotional reactions underlying social contacts are expected to play a role in communications on the social networks on the Web.
We present analysis of the empirical dataset  that we collected from MySpace networked dialogs and classified for the emotion content by ANEW methodology [1]. For theoretical analysis we devised an agent-based model, where the emotional agents [2] are adapted to the network environment and the rules of their  actions are reminiscent to those of the Web-based social networks, i.e., with a precise account of each message passed among the agents. Our results on both the empirical and the simulated data reveal user community structure and characteristic patterns of emotional behavior of the users (agents) in the phase space of 2-dimensional emotion variables, arousal and valence [1: M. Suvakov et al. (in preparation)]. [2: F. Schweitzer and D. Garcia, EPJB, vol. 77, 597 (2010)].

Cecilia Vernia

Inverse problem for interacting models in social sciences

How can Mathematics contribute to social science? Is it possible to describe social phenomena on solid scientific grounds? To address these questions,  I present  a mathematical framework for studying collective human behavior in situations where individuals are influenced by personal goals, cultural influences and norms, but also by social factors, such as peer pressure and herding effects. This goal will be achieved by integrating well known econometric tools  with mathematical techniques derived from theoretical physics, in particular from statistical mechanics.  Starting from real data coming from the Italian national health system and using the inverse problem  method, I try to evaluate how people respond to screening invitations. The considered models will assess the relative importance of different factors in making a given choice (e.g. taking a test for the prevention of cancer), including peer-to-peer influences (family, acquaintance, etc...), cultural heritage, public information campaigns and so on.  The ultimate goal of this study should be, for example, to determine the optimal allocation of resources for health prevention.

PRESENTATION

Paul Wouters

Modelling research practices - the case of peer review 

In this talk I will discuss two aspects of a running project on modelling the peer review process. First, I will discuss the merits and limitations of agent based modelling compared of other forms of modelling such as mathematical modelling. This will be done from the perspective of a reflexive constructivist framework of research. It is not self-evident how modelling as a methodology can fit within such a framework, since constructivism questions the assumptions that are often taken for granted in simulation research. I will show that models and simulations can nevertheless contribute in important ways to a thoroughly constructivist analysis of science and technology.

Second, I will discuss the state of affairs in modelling the scientific system itself. The presentation will conclude with a few examples from our current research project.

PRESENTATION

Sally Wyatt

On track: living and measuring everyday complexity

From the perspective of the recent ‘mobilities turn’ in social sciences, everyday life involves mobility – people travel daily to go to work, to shop, to meet friends or go to the dentist. This presentation will present the results of a recent study which developed new concepts and methods for analysing the ways in which people draw upon a range of resources to manage everyday mobility. The analysis builds on insights from time-geography, mobility studies and actor-network-theory to develop a conceptual vocabulary for understanding the dynamic and situated nature of travel in everyday life. The study combines qualitative and quantitative data from a study of hypermobile people in the Netherlands.

PRESENTATION

Oleg Yordanov

Dynamics of public opinion under different conditions

We study the model for public opinion dynamics in the presents of inflexible minorities under various conditions. In contrast to the majority of the citizens, the inflexible Andrei Anghelupeople never change their view on a particular issue, see references [1,2].  First, we consider in detail the versions of the model with sizes of the discussion groups four and five, for which we compute and present full phase diagrams for typical fractions of the “hard-core” devotees. Next, we introduce  a modification of the model which allows for a variable size discussion groups. Compared to the model of discussion group size k, the version involves k-1 additional parameters and a richer behavior.   The model is analyzed by a combination of numerical and analytical methods.  Finally, we extend the general sequential probabilistic model [3] as to incorporate inflexible majorities and present representative behaviors.
References:
[1] S. Galam, F. Jacobs, Physica A 381, 366-376 (2007).
[2] S. Galam, Physica A 389, 3619-3631 (2010).
[3] S. Galam,  Europhys. Lett. 70 (6), 705-711 (2005).

PRESENTATION

Poster:

Andrei Angheluta