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BEGIN:VEVENT
SUMMARY:Bi-layer temporal model of echo chambers and polarisation
DTSTART;VALUE=DATE-TIME:20210702T150000Z
DTEND;VALUE=DATE-TIME:20210702T150100Z
DTSTAMP;VALUE=DATE-TIME:20240806T135226Z
UID:indico-contribution-22-204@indico.fis.agh.edu.pl
DESCRIPTION:Speakers: Łukasz Gajewski (Warsaw University of Technology)\n
Echo chambers and polarisation dynamics are as of late a very prominent to
pic in scientific communities around the world. As these phenomena directl
y affect our lives\, and seemingly more and more as our societies and comm
unication channels evolve\, it becomes ever so important to understand the
intricacies of novel opinion dynamics in the modern era. We build upon an
existing echo chambers and polarisation model and extend it onto a bi-lay
er topology allowing us to indicate the possible consequences of two inter
acting groups. We develop both agent-based simulations and mean field solu
tions showing that there are conditions in which the system can reach stat
es of a neutral or polarised consensus\, a polarised opposition\, and even
opinion oscillations.\n\nhttps://indico.fis.agh.edu.pl/event/69/contribut
ions/204/
LOCATION:ONLINE
URL:https://indico.fis.agh.edu.pl/event/69/contributions/204/
END:VEVENT
BEGIN:VEVENT
SUMMARY:Three-state opinion q-voter model with bounded confidence
DTSTART;VALUE=DATE-TIME:20210702T150100Z
DTEND;VALUE=DATE-TIME:20210702T150200Z
DTSTAMP;VALUE=DATE-TIME:20240806T135226Z
UID:indico-contribution-22-205@indico.fis.agh.edu.pl
DESCRIPTION:Speakers: Maciej Doniec (wrocław university of science and te
chnology)\, Wojciech Radosz (Wroclaw University of Science and Technology)
\nWe study the q-voter model with bounded confidence on the complete graph
. Agents can be in one of three states. Two types of agents behaviour are
investigated: conformity and independence. We analyze whether this system
is qualitatively different from a corresponding model without bounded conf
idence. Our main results are the following. Firstly\, the system has two p
hase transitions: one between order-order phases and another between order
-disorder phases. Secondly\, the first transition is discontinuous in all
analyzed cases\, while the type of second transition depends on the size o
f group of influence.\n\nhttps://indico.fis.agh.edu.pl/event/69/contributi
ons/205/
LOCATION:ONLINE
URL:https://indico.fis.agh.edu.pl/event/69/contributions/205/
END:VEVENT
BEGIN:VEVENT
SUMMARY:Bias reduction in covariance matrices and its effects on high-dime
nsional portfolios.
DTSTART;VALUE=DATE-TIME:20210702T150300Z
DTEND;VALUE=DATE-TIME:20210702T150400Z
DTSTAMP;VALUE=DATE-TIME:20240806T135226Z
UID:indico-contribution-22-207@indico.fis.agh.edu.pl
DESCRIPTION:Speakers: Benito Rodriguez Camejo (CIMAT Monterrey)\nThe curre
nt world keeps evolving\, and in our era the challenge of "too much data"
keeps popping up\, in particular in the world of portfolio optimization\,
therein lies the opportunity of providing more accurate results through th
e use of the relatively new tools developed in the random matrix theory li
terature to reduce the bias in the sample covariance matrix of some financ
ial data (real or simulated). In this poster we will present a couple of t
hese tools and a brief summary of the results that can be achieved with th
em.\n\nIn this work we will apply the clipping\, Tracy-Widom\, linear shri
nkage and non linear shrinkage techniques as our bias reduction mechanisms
\, and then to compare their efficacy we will compare them by using the re
sulting estimators of the underlying covariance matrix to optimize our fin
ancial portfolios.\n\nThe financial portfolio model we use is the classic
Markowitz model with fixed returns of one for all our assets and we use tw
o variants\, the first one with the only restriction that we must assign a
ll of our capital into our selected assets\, and the second one with the s
ame restriction plus a second one in which we do not consider short sellin
g or more specifically that we can only buy assets. \n\nThe data that we u
se also consists of synthetic and real data\, the synthetic data consists
of two types the first one is structured gaussian and the second one is fr
om a simulated GARCH time series \, while the real data consists of two po
rtfolios one considering only traditional stocks and the other with a mix
of stocks and cryptocurrencies.\n\nWe hope to determine the efficacy of th
e bias reduction techniques to optimize financial data under multiple scen
arios.\n\nhttps://indico.fis.agh.edu.pl/event/69/contributions/207/
LOCATION:ONLINE
URL:https://indico.fis.agh.edu.pl/event/69/contributions/207/
END:VEVENT
BEGIN:VEVENT
SUMMARY:From relation to interactions: a case study in Reddit website
DTSTART;VALUE=DATE-TIME:20210702T150800Z
DTEND;VALUE=DATE-TIME:20210702T150900Z
DTSTAMP;VALUE=DATE-TIME:20240806T135226Z
UID:indico-contribution-22-228@indico.fis.agh.edu.pl
DESCRIPTION:Speakers: Robert Jankowski (Faculty of Physics\, Warsaw Univer
sity of Technology)\nElucidating what factors are salient in emerging inte
ractions in social networks is still an open question. Thus\, we develop a
n agent-based model for generating interactions in signed networks. The AB
Ms\, based on the Activity Driven Network model\, use signed relations bet
ween agents to reproduce their interaction frequencies and crucial network
distributions. The calibration and validation step is performed on the Re
ddit Hyperlink network\, where agents are represented by subreddits (commu
nities)\, and links by hyperlinks between communities. We devise a profoun
d methodology to assess the performance of the models. The proposed ABM su
ccessfully reproduces basic node-link and higher-order statistics of the e
mpirical dataset.\n\nhttps://indico.fis.agh.edu.pl/event/69/contributions/
228/
LOCATION:ONLINE
URL:https://indico.fis.agh.edu.pl/event/69/contributions/228/
END:VEVENT
BEGIN:VEVENT
SUMMARY:Diffusion of innovation on networks: agent-based vs. analytical ap
proach
DTSTART;VALUE=DATE-TIME:20210702T150200Z
DTEND;VALUE=DATE-TIME:20210702T150300Z
DTSTAMP;VALUE=DATE-TIME:20240806T135226Z
UID:indico-contribution-22-206@indico.fis.agh.edu.pl
DESCRIPTION:Speakers: Mikołaj Szurlej (Wrocław University of Science and
Technology)\, Angelika Abramiuk-Szurlej (Wrocław University of Science a
nd Technology)\nWe study an agent-based model of innovation diffusion on t
he Watts-Strogatz random graphs. The model is based on the $q$-voter model
with a noise (with nonconformity\, in the terminology of social psycholog
y)\, which has been previously used to describe the diffusion of green pro
ducts and practices. It originates from the $q$-voter model with independe
nce\, known also as the noisy nonlinear voter or the noisy $q$-voter model
. In the original model states $\\uparrow$ (yes/agree) and $\\downarrow$ (
no/disagree) are symmetrical and in case of independent behaviour each of
them is taken with the same probability. However\, when the model is used
to describe diffusion of innovation the up-down symmetry is broken. We inv
estigate the model analytically via mean-field approximation\, which gives
the exact result in case of a complete graph\, as well as via more advanc
ed method called pair approximation to determine how the average degree of
the network influences the process of diffusion of innovation. Additional
ly\, we conduct Monte Carlo simulations to check in which cases the agent-
based model can be reduced to the analytical one and when it cannot be don
e. We obtain the $S$-shaped curve of the number of adopters in time that a
grees with empirical observations. We also highlight that the time needed
for adoption depends on model parameters. Furthermore\, we present the tra
jectories and the stationary concentration of adopted for different sets o
f parameters to systematically analyze the model and determine when the ad
option would fail.\n\nAcknowledgement\nThis research is supported by proje
ct “Diamentowy Grant” DI2019 0150 49 financed by Polish Ministry of Sc
ience and Higher Education.\n\nhttps://indico.fis.agh.edu.pl/event/69/cont
ributions/206/
LOCATION:ONLINE
URL:https://indico.fis.agh.edu.pl/event/69/contributions/206/
END:VEVENT
BEGIN:VEVENT
SUMMARY:The spread of ideas in a network – the garbage can model
DTSTART;VALUE=DATE-TIME:20210702T150400Z
DTEND;VALUE=DATE-TIME:20210702T150500Z
DTSTAMP;VALUE=DATE-TIME:20240806T135226Z
UID:indico-contribution-22-208@indico.fis.agh.edu.pl
DESCRIPTION:Speakers: Dorota Żuchowska-Skiba (AGH Kraków)\nThe main goal
of our work is to show how ideas change in social networks. Our analysis
is based on three concepts: (i) temporal networks [1]\, (ii) the Axelrod m
odel of culture dissemination [2]\, (iii) the garbage can model of organiz
ational choice [3]. The use of the concept of temporal networks allows us
to show the dynamics of ideas spreading processes in networks\, thanks to
the analysis of contacts between agents in networks. The Axelrod culture d
issemination model allows us to use the importance of cooperative behavior
for the dynamics of ideas disseminated in networks. In the third model d
ecisions on solutions of problems are made as an outcome of sequences of p
seudorandom numbers. The origin of this model is the Herbert Simon’s vie
w on bounded rationality [4]. \nIn the Axelrod model\, ideas are conveyed
by chains of symbols. The outcome of the model should be the diversity of
evolving ideas as dependent on the chain length\, on the number of possib
le values of symbols and on the threshold value of Hamming distance which
enables the combination. \n\n[1] P. Holme and J. Saramaki\, Temporal netwo
rks\, Phys. Rep. 519\, 97 (2012).\n[2] R. Axelrod\, The dissemination of c
ulture: a model of local convergence and global polarization\, J. of Confl
ict Resolution 41\, 203 (1997).\n[3] M. D. Cohen\, J. G. March and J.P. Ol
sen\, A garbage can model of organizational choice\, Administrative Scien
ce Quarterly 17\, 1 (1972).\n[4] H. A. Simon\, A behavioral theory of rati
onal choice\, The Quarterly J. of Economics 69\, 99 (1955).\n\nhttps://ind
ico.fis.agh.edu.pl/event/69/contributions/208/
LOCATION:ONLINE
URL:https://indico.fis.agh.edu.pl/event/69/contributions/208/
END:VEVENT
BEGIN:VEVENT
SUMMARY:How social interactions lead to polarized relations?
DTSTART;VALUE=DATE-TIME:20210702T151000Z
DTEND;VALUE=DATE-TIME:20210702T151100Z
DTSTAMP;VALUE=DATE-TIME:20240806T135226Z
UID:indico-contribution-22-230@indico.fis.agh.edu.pl
DESCRIPTION:Speakers: Maciej Pawlik (Faculty of Physics\, Warsaw Universit
y of Technology )\nIn the age of social media there is more and more need
to understand how do people create relations using those. The objective he
re was not only to look if relations are being created as a consequence of
social interactions\, but also to separate emergence of positive and nega
tive relations. The knowledge we can gain here could benefit a wide spectr
um of applications - from purely scietific to business. \nIn this work we
used a dataset from Epinions website. In this dataset users of the website
can create articles\, rate them and declare trust or distrust towards oth
er users. The consequence of giving somebody a distrust rating is to reduc
e the probability to see their articles in the future. In the model users
are treated as agents in a network. They can be connected via signed edges
which represent existence and polarization of their relations.\nThe focus
of this work was put on the period where the declaration of trust was not
yet established\, as the impact of recommendation algorithm had to be avo
ided. We found that for any relation to be created\, two agents/users need
to interact more with each other. It might be counterintuitive if we thin
k of negative relations as a consequence of avoiding the other person.\nTh
is research is one of the first steps in our more thorough work directed a
t understanding the topic of polarized relations and interactions.\nThis r
esearch received funding from National Science Centre\, Poland Grant No. 2
019/01/Y/ST2/00058.\n\nhttps://indico.fis.agh.edu.pl/event/69/contribution
s/230/
LOCATION:ONLINE
URL:https://indico.fis.agh.edu.pl/event/69/contributions/230/
END:VEVENT
BEGIN:VEVENT
SUMMARY:Hierarchy depth in directed networks
DTSTART;VALUE=DATE-TIME:20210702T151300Z
DTEND;VALUE=DATE-TIME:20210702T151400Z
DTSTAMP;VALUE=DATE-TIME:20240806T135226Z
UID:indico-contribution-22-233@indico.fis.agh.edu.pl
DESCRIPTION:Speakers: Krzysztof Suchecki (Warsaw University of Technology)
\nThe term "hierarchy" when applied to networks can mean one of the few st
ructures: simple order hierarchy meaning ordering of elements\, nested hie
rarchy that is multi-level community structure or flow hierarchy defined b
y directed links that show causal or control structure in the network.\nWe
introduce two measures of node depth for flow hierarchy in directed netwo
rks\, measuring the level of hierarchy the nodes belong to. Rooted depth i
s defined as distance from specific root node and relative depth relies on
directed links serving as "target node has larger depth than source" rela
tions.\nWe explore the behavior of these two measures\, their properties a
nd differences between them. To cope with eventual directed loops in the n
etworks we introduce loop-collapse method\, that evens out depth values fo
r all nodes in the same directed loop.\nWe investigate the behavior of the
introduced depth measures in random graphs of different sizes and densiti
es as well as some real network topologies. Maximum depth depends on netwo
rk density\, first increasing with mean degree\, up to percolation thresho
ld and declining afterwards as the number of loops increase.\n\nhttps://in
dico.fis.agh.edu.pl/event/69/contributions/233/
LOCATION:ONLINE
URL:https://indico.fis.agh.edu.pl/event/69/contributions/233/
END:VEVENT
BEGIN:VEVENT
SUMMARY:Scalable learning of independent cascade dynamics from partial obs
ervations
DTSTART;VALUE=DATE-TIME:20210702T151400Z
DTEND;VALUE=DATE-TIME:20210702T151500Z
DTSTAMP;VALUE=DATE-TIME:20240806T135226Z
UID:indico-contribution-22-234@indico.fis.agh.edu.pl
DESCRIPTION:Speakers: Mateusz Wilinski (Los Alamos National Laboratory)\nS
preading processes play an increasingly important role in modeling for dif
fusion networks\, information propagation\, marketing and opinion setting.
We address the problem of learning of a spreading model such that the pre
dictions generated from this model are accurate and could be subsequently
used for the optimization\, and control of diffusion dynamics. Unfortunate
ly\, full observations of the dynamics are rarely available. As a result\,
standard approaches such as maximum likelihood quickly become intractable
for large network instances. We introduce a computationally efficient alg
orithm\, based on a scalable dynamic message-passing approach\, which is a
ble to learn parameters of the effective spreading model given only limite
d information on the activation times of nodes in the network. We show tha
t tractable inference from the learned model generates a better prediction
of marginal probabilities compared to the original model. We develop a sy
stematic procedure for learning a mixture of models which further improves
prediction quality of the model.\n\nMore details at:\nhttps://arxiv.org/p
df/2007.06557.pdf\n\nhttps://indico.fis.agh.edu.pl/event/69/contributions/
234/
LOCATION:ONLINE
URL:https://indico.fis.agh.edu.pl/event/69/contributions/234/
END:VEVENT
BEGIN:VEVENT
SUMMARY:Generic Features in the Spectral Decomposition of Correlation Matr
ices
DTSTART;VALUE=DATE-TIME:20210702T152100Z
DTEND;VALUE=DATE-TIME:20210702T152200Z
DTSTAMP;VALUE=DATE-TIME:20240806T135226Z
UID:indico-contribution-22-242@indico.fis.agh.edu.pl
DESCRIPTION:Speakers: Yuriy Stepanov ()\nWe show that correlation matrices
with particular average and variance of the correlation coefficients hav
e a notably restricted spectral structure. Applying geometric methods\, w
e derive lower bounds for the largest eigenvalue and the alignment of the
corresponding eigenvector. We explain how and to which extent\, a distinc
tly large eigenvalue and an approximately diagonal eigenvector generically
occur for specific correlation matrices independently of the correlation
matrix dimension.\n\nhttps://indico.fis.agh.edu.pl/event/69/contributions/
242/
LOCATION:ONLINE
URL:https://indico.fis.agh.edu.pl/event/69/contributions/242/
END:VEVENT
BEGIN:VEVENT
SUMMARY:Finding optimal strategies in the Yard-Sale model using neuroevolu
tion techniques
DTSTART;VALUE=DATE-TIME:20210702T152000Z
DTEND;VALUE=DATE-TIME:20210702T152100Z
DTSTAMP;VALUE=DATE-TIME:20240806T135226Z
UID:indico-contribution-22-224@indico.fis.agh.edu.pl
DESCRIPTION:Speakers: Julian Neñer (Balseiro Institute)\nA new type of in
-depth microscopic analysis is presented for the Yard-Sale model\, one of
the most well known multi-agent market exchange models. This approach led
to the classification and study of the individual strategies carried out b
y the agents undergoing transactions\, as given by their risk propensity.
These findings allowed to determine a region of parameters for which the s
trategies are successful\, and in particular\, the existence of an optimal
strategy. To continue exploring this concept\, a new approach is then pro
posed in which rationality is added in the agents behaviour through machin
e learning techniques. Strategies that maximize the individual wealth of e
ach agent were then found by performing their training through a genetic a
lgorithm. The addition of different levels of rationality given by the amo
unt of available information from their environment showed new and promisi
ng results\, both at the macroscopic and microscopic level. It was found t
hat the addition of trained agents in these systems leads to an increase i
n wealth inequality at the collective level.\n\nhttps://indico.fis.agh.edu
.pl/event/69/contributions/224/
LOCATION:ONLINE
URL:https://indico.fis.agh.edu.pl/event/69/contributions/224/
END:VEVENT
BEGIN:VEVENT
SUMMARY:Multibranch multifractality and the phase transitions in the tradi
ng activity
DTSTART;VALUE=DATE-TIME:20210702T150600Z
DTEND;VALUE=DATE-TIME:20210702T150700Z
DTSTAMP;VALUE=DATE-TIME:20240806T135226Z
UID:indico-contribution-22-226@indico.fis.agh.edu.pl
DESCRIPTION:Speakers: Jarosław Klamut (University of Warsaw)\nEmpirical t
ime series of inter-event or waiting times are investigated using a modifi
ed Multifractal Detrended Fluctuation Analysis operating on fluctuations o
f mean detrended dynamics. The core of the extended multifractal analysis
is the non-monotonic behavior of the generalized Hurst exponent $h(q)$ --
the fundamental exponent in the study of multifractals. The consequence of
this behavior is the non-monotonic behavior of the coarse Hölder exponen
t $\\alpha (q)$ leading to multi-branchedness of the spectrum of dimension
s. The Legendre-Fenchel transform is used instead of the routinely used ca
nonical Legendre (single-branched) contact transform. Thermodynamic conseq
uences of the multi-branched multifractality are revealed. The results [1]
are presented for the high-frequency data from Polish stock market (Warsa
w Stock Exchange) for intertrade times for KGHM - one of the most liquid s
tocks there.\n\n[1] J. Klamut\, R. Kutner\, T. Gubiec\, and Z. R. Struzik\
, 'Multibranch multifractality and the phase transitions in time series of
mean interevent times'\, Phys. Rev. E 101\, 063303 (2020)\n\nhttps://indi
co.fis.agh.edu.pl/event/69/contributions/226/
LOCATION:ONLINE
URL:https://indico.fis.agh.edu.pl/event/69/contributions/226/
END:VEVENT
BEGIN:VEVENT
SUMMARY:Information Measure for Long Range Correlated Time Series
DTSTART;VALUE=DATE-TIME:20210702T150900Z
DTEND;VALUE=DATE-TIME:20210702T151000Z
DTSTAMP;VALUE=DATE-TIME:20240806T135226Z
UID:indico-contribution-22-229@indico.fis.agh.edu.pl
DESCRIPTION:Speakers: Pietro Murialdo (Politecnico di Torino)\nWe applied
the moving average cluster entropy to study long-range correlation\, dynam
ics and heterogeneity of financial time series\, and to propose an alterna
tive method to portfolio estimation.\n\nThe cluster entropy relies on the
Shannon entropy $S(P_i) = - \\sum_i P_i \\ln P_i$. The probability distrib
ution function of each asset $i$ is obtained intersecting the asset time s
eries $y(t)$ with its moving average series $y_n(t)$. The portion of time
series between two consecutive intersections of $y(t)$ and $y_n(t)$ is def
ined as a cluster. Then\, $P(\\tau\,n)$\, which associates clusters of dur
ation $\\tau$ to their frequency\, is fed into the Shannon entropy to obta
in the moving average cluster entropy. We summarize the results into the c
luster entropy index $I(n)$\, obtained integrating $S(\\tau\,n)$ over dura
tion $\\tau$.\n\nWe used high frequency financial time series of important
market indexes (NASDAQ\, DJIA\, S\\&P500\, ...) of 2018. To study their d
ynamics\, we analyzed twelve consecutive temporal horizon\, summing up to
a whole year. \n\nWe found positive long-range correlation for financial d
ata\, similar to fractional stochastic process with Hurst exponent $0.5\\l
eq H\\leq 1$.\nMoreover\, we compared our results to Kullback-Leibler entr
opy results based on the pricing kernel simulations for different represen
tative agent models.\n\nWe show that the cluster entropy of volatility ser
ies depends on the individual asset\, while the cluster entropy of price s
eries is invariant for different assets. Furthermore\, we propose the clus
ter entropy portfolio. Portfolio weights are obtained from the cluster ent
ropy index $I$. We also integrated horizon dependence. We show the cluster
entropy portfolio ability to adjust to market dynamics by varying asset a
llocation.\n\nhttps://indico.fis.agh.edu.pl/event/69/contributions/229/
LOCATION:ONLINE
URL:https://indico.fis.agh.edu.pl/event/69/contributions/229/
END:VEVENT
BEGIN:VEVENT
SUMMARY:In searching for possible relationships between the COVID-19 pande
mic and the currency exchange rates via the Dynamic Time Warping method
DTSTART;VALUE=DATE-TIME:20210702T152200Z
DTEND;VALUE=DATE-TIME:20210702T154200Z
DTSTAMP;VALUE=DATE-TIME:20240806T135226Z
UID:indico-contribution-22-243@indico.fis.agh.edu.pl
DESCRIPTION:Speakers: Arkadiusz Orłowski (Katedra Sztucznej Inteligencji\
, Instytut Informatyki Technicznej\, SGGW w Warszawie\, Poland)\nThe Covid
-19 pandemic has affected not only economies of particular countries but t
he entire world economic system. It is not surprising that also currency e
xchange rates are not left untouched by the current crisis. The main objec
tive of our study here is to assess the similarity between the time series
of currency exchange rates and the Covid-19 time series (e.g.\, we invest
igate the relationship between the Euro/USD exchange rate and the ratio of
Covid-19 daily cases in Eurozone and the USA). In other words\, we want t
o quantitatively know how various currency exchange rates are associated w
ith the observed development of the pandemic. To achieve this goal and to
check if and to what extent the Covid-19 spread is related to the exchange
rates\, we employ the Dynamic Time Warping (DTW) method. Making use of th
e DTW method\, a distance between analyzed time series can be defined and
calculated. Having such a distance makes it possible to group currencies a
ccording to their change relative to the pandemic dynamics. Time shifts be
tween daily Covid-19 events and currency exchange rates are also analyzed
within the framework of the developed formalism.\n\nhttps://indico.fis.agh
.edu.pl/event/69/contributions/243/
LOCATION:ONLINE
URL:https://indico.fis.agh.edu.pl/event/69/contributions/243/
END:VEVENT
BEGIN:VEVENT
SUMMARY:Archetypal analysis and classical segmentation methods. Comparison
of two approaches on financial data.
DTSTART;VALUE=DATE-TIME:20210702T151100Z
DTEND;VALUE=DATE-TIME:20210702T151200Z
DTSTAMP;VALUE=DATE-TIME:20240806T135226Z
UID:indico-contribution-22-231@indico.fis.agh.edu.pl
DESCRIPTION:Speakers: Urszula Grzybowska (Warsaw University of Life Scienc
es (SGGW))\nMacroeconomic analyses are\, to a large extent\, based on firm
segmentation and creating homogeneous groups of entities. Thanks to this
procedure one can estimate indicators (e.g.\, various Key Performance Indi
cators) with high accuracy and examine trends of the market. Unfortunately
\, the drawback is that segmentation algorithms based on distance measures
model average values and are not suitable to analysing unusual events. Mo
delling in Archetypal Analysis is done in a different way. Both approaches
are used e.g.\, in marketing research\, where on one hand one looks for t
arget groups and on the other hand introduces active techniques in form of
trend makers.\nArchetypal Analysis was introduced in 1994 by Cutler and B
reiman as a method that provides some kind of reference observations for g
iven data. Archetypes are extreme observations\, vertexes of convex hull o
f the data points obtained as a result of a two-stage nonlinear optimizati
on. \nThe aim of our research is to compare results of analyses done using
both\, segmentation methods and averaging forecasts and Archetypal Analys
is for firms listed on WSE and described by financial indicators (KPI). Th
e authors propose an approach that brings together advantages of both meth
ods. In order to compare Archetypal Analysis and the approach based on seg
mentation methods\, the authors used financial data.\n\nhttps://indico.fis
.agh.edu.pl/event/69/contributions/231/
LOCATION:ONLINE
URL:https://indico.fis.agh.edu.pl/event/69/contributions/231/
END:VEVENT
BEGIN:VEVENT
SUMMARY:Wealth transfer in an economy with two social groups
DTSTART;VALUE=DATE-TIME:20210702T151200Z
DTEND;VALUE=DATE-TIME:20210702T151300Z
DTSTAMP;VALUE=DATE-TIME:20240806T135226Z
UID:indico-contribution-22-232@indico.fis.agh.edu.pl
DESCRIPTION:Speakers: Thiago Dias (Universidade Tecnológica Federal do Pa
raná)\nSocial stratification\, the division of society into groups\, can
result from historical and social factors and reflect economic inequality.
Ethnicity\, gender\, and race are examples of subgroups where people belo
nging to one can be privileged in terms of status\, power\, and wealth. In
fact\, in many societies\, dominant classes are composed of many people a
ssociated with one group\, and economic inequality might be related to thi
s non-economical classification.\nWe study an agent model where pair of in
dividuals can exchange wealth with no underlying lattice. The wealth\, ris
k aversion factor\, and group of the agents characterize their state. The
wealth exchanged between two agents is calculated by a fair rule\, where b
oth agents put the same amount at stake\, i.e.\, no agent can win more tha
n he/she is willing to lose. We consider two subsystems\; interaction betw
een agents can be among members of the same group or with the other group
with different probabilities. Each subsystem has different protections to
the poor agent\, whereas the intergroup exchanges obey an exclusive protec
tion rule\, which can be understood as a public policy to reduce inequalit
y.\nOur results show that the most protected group shows more accumulated
wealth\, less inequality\, and its agents have more chances of economic mo
bility. Another significant result is that the agents on the less protecte
d group transfer their wealth to agents of the other group on average. The
amount transferred depends on the relation of group internal social prote
ction and the probability of agents of different groups interact.\n\nhttps
://indico.fis.agh.edu.pl/event/69/contributions/232/
LOCATION:ONLINE
URL:https://indico.fis.agh.edu.pl/event/69/contributions/232/
END:VEVENT
BEGIN:VEVENT
SUMMARY:Discontinuous phase transitions in the multi-state noisy q-voter m
odel: quenched vs. annealed disorder
DTSTART;VALUE=DATE-TIME:20210702T151500Z
DTEND;VALUE=DATE-TIME:20210702T151600Z
DTSTAMP;VALUE=DATE-TIME:20240806T135226Z
UID:indico-contribution-22-235@indico.fis.agh.edu.pl
DESCRIPTION:Speakers: Bartłomiej Nowak (Wrocław University of Science an
d Technology)\nWe introduce a generalized version of the noisy q-voter mod
el\, one of the most popular opinion dynamics models\, in which voters can
be in one of s≥2 states. As in the original binary q-voter model\, whic
h corresponds to s=2\, at each update randomly selected voter can conform
to its q randomly chosen neighbors (copy their state) only if all q neighb
ors are in the same state. Additionally\, a voter can act independently\,
taking a randomly chosen state\, which introduces disorder to the system.
We consider two types of disorder: (1) annealed\, which means that each vo
ter can act independently with probability p and with complementary probab
ility 1−p conform to others\, and (2) quenched\, which means that there
is a fraction p of all voters\, which are permanently independent and the
rest of them are conformists. We analyze the model on the complete graph a
nalytically and via Monte Carlo simulations. We show that for the number o
f states s>2 model displays discontinuous phase transitions for any q>1\,
on contrary to the model with binary opinions\, in which discontinuous pha
se transitions are observed only for q>5. Moreover\, unlike the case of s=
2\, for s>2 discontinuous phase transitions survive under the quenched dis
order\, although they are less sharp than under the annealed one.\n\nhttps
://indico.fis.agh.edu.pl/event/69/contributions/235/
LOCATION:ONLINE
URL:https://indico.fis.agh.edu.pl/event/69/contributions/235/
END:VEVENT
BEGIN:VEVENT
SUMMARY:Escaping polarization
DTSTART;VALUE=DATE-TIME:20210702T151600Z
DTEND;VALUE=DATE-TIME:20210702T151700Z
DTSTAMP;VALUE=DATE-TIME:20240806T135226Z
UID:indico-contribution-22-236@indico.fis.agh.edu.pl
DESCRIPTION:Speakers: Piotr Górski (Warsaw University of Technology\, Fac
ulty of Physics)\nOne of the challenges faced by today's societies is to d
eal with the growing polarization. Here\, we propose an agent-based model
incorporating theories of structural balance and homophily. Most of the li
terature identify a structurally balanced state as a polarized one. Howeve
r\, we show that these two states are not always equivalent. We study a mu
ltilayer system with one layer related to the agents' relations and the ot
hers to the similarity between agents. We define the polarization as the s
tate with two or more enemy groups in the relation layer and we study the
influence of different types of homophily in the similarity layers and hom
ophily strength on the fates of the system. We identify homophily types th
at are most efficient in limiting the system polarization. \nThis research
received funding from National Science Centre\, Poland Grant No. 2019/01/
Y/ST2/00058.\n\nhttps://indico.fis.agh.edu.pl/event/69/contributions/236/
LOCATION:ONLINE
URL:https://indico.fis.agh.edu.pl/event/69/contributions/236/
END:VEVENT
BEGIN:VEVENT
SUMMARY:The Economic Impact of Modern Maritime Piracy
DTSTART;VALUE=DATE-TIME:20210702T151800Z
DTEND;VALUE=DATE-TIME:20210702T151900Z
DTSTAMP;VALUE=DATE-TIME:20240806T135226Z
UID:indico-contribution-22-238@indico.fis.agh.edu.pl
DESCRIPTION:Speakers: Jana Meles (Politechnika Warszawa)\nI present the is
sue of quantifying the impact of modern maritime piracy practises on world
trade. For this purpose the case of Somali piracy is investigated. Data i
s carefully analysed with the statistical methodology of modern empirical
economics to identify the causal effect of pirate attacks on trade volumes
and transportation costs. This is a good example for the detection of sma
ll causal effects that are drowned out by much larger fluctuations in the
data\, if these are not carefully removed. Furthermore\, a gravity model f
or international trade is incorporated.\nI find that piracy substantially
reduces the amount of goods shipped through the affected area (average ann
ual trade reduction of 4.3 billion USD from 2000 to 2019)\, while no signi
ficant effect on transportation cost can be found.\nThis research was cond
ucted as part of my Master's thesis and is of relevance due to the long on
going issue of appropriate anti-piracy measures. [T. Besley\, T. Fetzer\,
and H. Mueller\, "The welfare cost of lawlessness: Evidence from Somali Pi
racy"\, Journal of the European Economic Association 2015\; A. Burlando\,
A. D. Cristea\, and L. M. Lee\, "The Trade Consequences of Maritime Insecu
rity: Evidence from Somali Piracy"\, Review of International Economics 201
5]\n\nhttps://indico.fis.agh.edu.pl/event/69/contributions/238/
LOCATION:ONLINE
URL:https://indico.fis.agh.edu.pl/event/69/contributions/238/
END:VEVENT
BEGIN:VEVENT
SUMMARY:Discontinous phase transitions in the generalized q-voter model on
random graphs
DTSTART;VALUE=DATE-TIME:20210702T150700Z
DTEND;VALUE=DATE-TIME:20210702T150800Z
DTSTAMP;VALUE=DATE-TIME:20240806T135226Z
UID:indico-contribution-22-227@indico.fis.agh.edu.pl
DESCRIPTION:Speakers: Jakub Pawłowski (Wrocław University of Science and
Technology)\, Arkadiusz Lipiecki (Wrocław University of Science and Tech
nology)\nWe investigate the binary $q$-voter model with generalized antico
nformity on random Erdős–Rényi graphs. The generalization refers to th
e freedom of choosing the size of the influence group independently for th
e case of conformity $q_c$ and anticonformity $q_a$. This model was studie
d before on the complete graph\, which corresponds to the mean-field appro
ach\, and on such a graph discontinuous phase transitions were observed fo
r $q_c>q_a + \\Delta q$\, where $\\Delta q=4$ for $q_a \\le 3$ and $\\Delt
a q=3$ for $q_a>3$. Examining the model on random graphs allows us to answ
er the question whether a discontinuous phase transition can survive the s
hift to a network with the value of average node degree that is observed i
n real social systems. By approaching the model both within Monte Carlo (M
C) simulations and Pair Approximation (PA)\, we are able to compare the re
sults obtained within both methods and to investigate the validity of PA.
We show that as long as the average node degree of a graph is relatively l
arge\, PA overlaps MC results. On the other hand\, for smaller values of t
he average node degree\, PA gives qualitatively different results than Mon
te Carlo simulations for some values of $q_c$ and $q_a$. In such cases\, t
he phase transition observed in the simulation is continuous on random gra
phs as well as on the complete graph\, whereas PA indicates a discontinuou
s one. We determine the range of model parameters for which PA gives incor
rect results and we present our attempt at validating the assumptions made
within the PA method in order to understand why PA fails\, even on the ra
ndom graph.\n\nhttps://indico.fis.agh.edu.pl/event/69/contributions/227/
LOCATION:ONLINE
URL:https://indico.fis.agh.edu.pl/event/69/contributions/227/
END:VEVENT
BEGIN:VEVENT
SUMMARY:Weighted Axelrod model
DTSTART;VALUE=DATE-TIME:20210702T154200Z
DTEND;VALUE=DATE-TIME:20210702T155500Z
DTSTAMP;VALUE=DATE-TIME:20240806T135226Z
UID:indico-contribution-22-245@indico.fis.agh.edu.pl
DESCRIPTION:Speakers: Zuzanna Kalinowska (Faculty of Physics\, Astronomy a
nd Applied Computer Science\, Jagiellonian University)\nThe Axelrod model
is a well known model of culture development and dissemination describing
a possible mechanism for emergence of cultural domains. It is based on t
wo sociological phenomena: homophily and the theory of social influence. T
echnically\, it assumes that every culture is represented by a vector of F
cultural traits (features)\, each taking any of q allowed opinions (value
s). The model assumes that an individual can interact with local neighbors
if they share common traits. The agents are conservative in the sense th
at they are more likely to interact with other agents who are similar to t
hem. At every successful interaction\, one of the interacting agents accep
ts the agent’s point of view on a topic on which both agents differ. Con
sequently\, interactions increase the similarity between agents and make t
hem even more likely to interact in the future. The Axelrod model allows f
or coexistence of multiple cultural domains where neighboring cultures are
completely different.\n\n\nThe Axelrod model does not take into account
the fact that cultural attributes may have different significance for a gi
ven individual. This is a limitation in the context of how the model refle
cts the mechanisms driving the evolution of real societies. The model is m
odified by giving individual features different weights that have a decisi
ve impact on the possibility of changing the opinion and in turn on intera
ctions between two individuals. Introduced weights have a significant impa
ct on the system evolution\, in particular they increase the polarization
of the system in the final state.\n\n\n[1] R. Axelrod\, J. Conflict Resolt
. 41\, 203 (1997).\n[2] B. Dybiec\, N. Mitarai and K. Sneppen\, Eur. Phys.
J. B 85\, 357 (2012).\n\nhttps://indico.fis.agh.edu.pl/event/69/contribut
ions/245/
LOCATION:ONLINE
URL:https://indico.fis.agh.edu.pl/event/69/contributions/245/
END:VEVENT
END:VCALENDAR