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  • DELANOË Alexandre (3)
  • CHEON Taksu (2)
  • TIMPANARO André (2)
  • VINOGRADOVA Galina (2)
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in Physica A: Statistical Mechanics and its Applications Publié en 2021
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This paper predicting Trump victory has been submitted before the election and revised after, allowing to add a Foreword and Note Added in Revision to discuss in details both the causes of the failure of the prediction and what has been robust in its making. In 2016, Trump was unanimously seen as the loser in the November 8 election. In contrast, using a model of opinion dynamics I have been developing for a few decades within the framework of sociophysics, I predicted his victory against all odds. According to the model, the winning paradoxical martingale of 2016, has been Trump capability to activate frozen prejudices in many voters by provoking their real indignation. However, four year later, Trump “shocking” outings do not shock anymore, they became devitalized, losing their ability to generate major emotional reactions. Does this mean that this time around he will lose the 2020 election against Biden, as nearly all analysts, pundits and commentators still predict? No, because with frozen prejudices remaining frozen, the spontaneous prejudices will be activated but this time they will benefit to both Biden and Trump. The main ones are the fear of the other candidate policy and the personal stand facing a danger. In addition, Trump presidency having polarized a large part of American voters into narrow-minded anti-Trump and narrow-minded pro-Trump, those I denote in my model as inflexibles, will be driving the dynamics of choices. Both effects, prejudices and inflexibles can either compete or cooperate making their local combination within each state, decisive to determine the faith of the state election. As a result, tiny differences can make the outcome. Based on my rough estimates of associated proportions of inflexibles and prejudices, the model predicts Trump victory in the 2020 November election.

in Frontiers in physics Publié en 2020-11
CHEONG Kee-Cheok
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A universal formula is shown to predict the dynamics of public opinion including eventual sudden and unexpected outbreaks of minority opinions within a generic parameter space of five dimensions. The formula is obtained combining and extending several components of Galam model of opinion dynamics, otherwise treated separately, into one single update equation, which then deploys in a social space of five dimensions. Four dimensions account for a rich diversity of individual traits within a heterogeneous population, including differentiated stubbornness, contrarianism, and embedded prejudices. The fifth dimension is the size for the discussing update groups. Having one single formula allows exploring the complete geometry of the underlying landscape of opinion dynamics. Attractors and tipping points, which shape the topology of the different possible dynamics flows, are unveiled. Driven by repeated discussions among small groups of people during a social or political public campaign, the phenomenon of minority spreading and parallel majority collapse are thus revealed ahead of their occurrence. Accordingly, within the opinion landscape, unexpected and sudden events like Brexit and Trump victories become visible within a forecast time horizon making them predictable. Despite the accidental nature of the landscape, evaluating the parameter values for a specific case allows to single out which basin of attraction is going to drive the associate dynamics and thus a prediction of the outcome becomes feasible. The model may apply to a large spectrum of social situations including voting outcomes, market shares and societal trends, allowing to envision novel winning strategies in competing environments.

in Physica A: Statistical Mechanics and its Applications Publié en 2020-09
TIETZE A
HOFMANN P
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A fair assignment of credit for multi-authored publications is a long-standing issue in scientometrics. In the calculation of the -index, for instance, all co-authors receive equal credit for a given publication, independent of a given author’s contribution to the work or of the total number of co-authors. Several attempts have been made to distribute the credit in a more appropriate manner. In a recent paper, Hirsch has suggested a new way of credit assignment that is fundamentally different from the previous ones: All credit for a multi-author paper goes to a single author, the called “-author”, defined as the person with the highest current -index (not the highest -index at the time of the paper’s publication) (Hirsch, 2019). The collection of papers this author has received credit for as -author is then used to calculate a new index, following the same recipe as for the usual index. The objective of this new assignment is not a fairer distribution of credit, but rather the determination of an altogether different property, the degree of a person’s scientific leadership. We show that given the complex time dependence of for individual scientists, the approach of using the current value instead of the historic one is problematic, and we argue that it would be feasible to determine the -author at the time of the paper’s publication instead. On the other hand, there are other practical considerations that make the calculation of the proposed very difficult. As an alternative, we explore other ways of crediting papers to a single author in order to test early career achievement or scientific leadership.

in Chaos: An Interdisciplinary Journal of Nonlinear Science Publié en 2020-07
ZEHMAKAN Ahad
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The dynamics of rumor spreading is investigated using a model with three kinds of agents who are, respectively, the Seeds, the Agnostics, and the Others. While Seeds are the ones who start spreading the rumor being adamantly convinced of its truth, Agnostics reject any kind of rumor and do not believe in conspiracy theories. In between, the Others constitute the main part of the community. While Seeds are always Believers and Agnostics are always Indifferents, Others can switch between being Believer and Indifferent depending on who they are discussing with. The underlying driving dynamics is implemented via local updates of randomly formed groups of agents. In each group, an Other turns into a Believer as soon as m or more Believers are present in the group. However, since some Believers may lose interest in the rumor as time passes by, we add a flipping fixed rate 0

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Si le manque de masque est admis, il est affirmé qu’ils ne sont nécessaires que pour les soignants. Mais si on en avait suffisamment, il serait demandé à tout le monde d’en porter car toute réduction des contaminations est décisive face à la propagation. (premières lignes)

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En 2016 les victoires du Brexit et de Trump ont porté un coup sérieux à la capacité prédictive de la plupart des analystes, experts et sondeurs qui ne les avaient pas prévues. Ces votes ont été des événements imprévus qui ne figuraient pas parmi la liste des possibles. Le même type de phénomène soudain et imprévu s’est produit avec le mouvement des Gilets Jaunes en France ainsi que le rejet massif dans la rue algérienne d’un cinquième mandat consécutif du Président en exercice. Parallèlement, certains événements tout aussi inattendus à un moment donné peuvent devenir prévisibles par les sondages à un autre moment plus tardif mais qui reste antérieur à l’échéance électorale, même s’ils restent considérés comme anormaux. L’élection massive à la présidence ukrainienne d’un comédien mettant en scène le président de l’Ukraine dans une série télévisée en est une parfaite illustration. À partir d’un modèle de dynamique d’opinion, je montre que ces deux types de phénomènes « anormaux » sont produits par le déploiement d’une non-linéarité dans l’évolution temporelle des distributions d’opinion des différents choix concurrents. La différence discriminante entre les deux étant le moment de l’émergence de la rupture dans la dynamique d’opinion par rapport au vote. Cela signifie qu'une connaissance des équations régissant la dynamique d’opinion permet en principede prévoir ce qui parait imprévisible. Cependant, dans certains cas, même avec les bonnes équations, la prédiction devient aléatoire en raison d’un flou incompressible dans l’évaluation de certains paramètres.

in Entropy Publié en 2020-01
CHEON Taksu
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Asymmetry in contrarian behavior is investigated within the Galam model of opinion dynamics using update groups of size 3 with two competing opinions A and B. Denoting x and y the respective proportions of A and B contrarians, four schemes of implementations are studied. The first scheme activates contrarians after each series of updates with probabilities x and y for agents holding respectively opinion A and B. Second scheme activates contrarians within the update groups only against global majority with probability x when A is the majority and y when B is the majority. The third scheme considers in-group contrarians acting prior to the local majority update against both local majority and minority opinions. The last scheme activates in-group contrarians prior to the local majority update but only against the local majority. The main result is the loss of the fifty–fifty attractor produced by symmetric contrarians. Producing a bit less contrarians on its own side than the other side becomes the key to win a public debate, which in turn can guarantee an election victory. The associated phase diagram of opinion dynamics is found to exhibit a rich variety of counterintuitive results.

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We assume a community whose members adopt one of two opinions A or B. Each member appears as an inflexible, or as a non-contrarian or contrarian floater. An inflexible sticks to its opinion, whereas a floater may change into a floater of the alternative opinion. The occurrence of this change is governed by the local majority rule: members meet in groups of a fixed size, and a floater then changes its opinion provided it is a minority in the group. Subsequently, a non-contrarian floater keeps the opinion as adopted under the local majority rule, whereas a contrarian floater adopts the alternative opinion. Whereas the effects of on the one hand inflexibles and on the other hand non-contrarians and contrarians have previously been studied seperately, the current approach allows us to gain insight in the effect of their combined presence in a community. Given fixed proportions of inflexibles (αA,αB) for the two opinions, and fixed fractions of contrarians (γA,γB) among the A and B floaters, we derive the update equation pt+1 for the overall support for opinion A at time t+1, given pt. The update equation is derived respectively for local group sizes 1, 2 and 3. The associated dynamics generated by repeated local updates is then determined to identify its asymptotic steady configuration. The full opinion flow diagram is thus obtained, showing conditions in terms of the parameters for each opinion to eventually win the competing dynamics. Various dynamical scenarios are thus exhibited, and it is derived that relatively small densities of inflexibles allow for more variation in the qualitative outcome of the dynamics than higher densities of inflexibles.

in Physics letters. A Publié en 2018-06
CHEON Taksu
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We introduce a model of temporal evolution of political opinions which amounts to a dynamical extension of Galam model in which the proportions of inflexibles are treated as dynamical variables. We find that the critical value of inflexibles in the original Galam model now turns into a fixed point of the system whose stability controls the phase trajectory of the political opinions. The appearance of two phases is found, in which majority-preserving and regime-changing limit cycles are respectively dominant, and the phase transition between them is observed.

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I revisit the 2017 French Presidential election which opposed the far right National Front candidate Marine Le Pen against the center candidate Emmanuel Macron. While voting intentions for Le Pen stuck below 50% and polls kept predicting her failure, I warned on the emergence of a novel phenomenon I defined as unavowed abstention, which could suddenly reverse the ranking at Le Pen benefit on the voting day. My warning got a massive media coverage. She eventually lost the runoff at a score worse than predicted by the polls. Using a quantitative mathematical framing, which reveals the existence of tipping points in respective turnouts, I show that the predicted phenomenon of unavowed abstention did happen. But instead of shattering the expected outcome, against all odds it occurred at Le Pen expense, therefore without impact on the final outcome. The results shed a new light on other national cases such as Obama and Trump victories in the US.

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