3499 research outputs found
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It’s Always April Fools’ Day! On the Difficulty of Social Network Misinformation Classification via Propagation Features
No full textGiven the huge impact that Online Social Networks (OSN)
had in the way people get informed and form their opinion,
they became an attractive playground for malicious entities
that want to spread misinformation, and leverage their effect.
In fact, misinformation easily spreads on OSN and is a huge
threat for modern society, possibly influencing also the outcome
of elections, or even putting people’s life at risk (e.g.,
spreading “anti-vaccines” misinformation). Therefore, it is
of paramount importance for our society to have some sort
of “validation” on information spreading through OSN. The
need for a wide-scale validation would greatly benefit from
automatic tools.
In this paper, we show that it is difficult to carry out an automatic
classification of misinformation considering only structural
properties of content propagation cascades. We focus on
structural properties, because they would be inherently dif-
ficult to be manipulated, with the the aim of circumventing
classification systems. To support our claim, we carry out an
extensive evaluation on Facebook posts belonging to conspiracy
theories (as representative of misinformation), and scientific
news (representative of fact-checked content). Our
findings show that conspiracy content actually reverberates
in a way which is hard to distinguish from the one scientific
content does: for the classification mechanisms we investigated,
classification F1-score never exceeds 0.65 during content
propagation stages, and is still less than 0.7 even after
propagation is complete
Networks of reinforced stochastic processes: Asymptotics for the empirical means
No full textThis work deals with systems of interacting reinforced stochastic processes, where each process X^j = (X_{n,j})_n is located at a vertex j of a finite weighted direct graph, and it can be interpreted as the sequence of “actions” adopted by an agent j of the network. The interaction
among the evolving dynamics of these processes depends on the weighted adjacency matrix W associated to the underlying graph: indeed, the probability that an agent j chooses a certain action depends on its personal “inclination” Z_{n,j} and on the inclinations Z_{n,h} , with h not equal to j, of the other agents according to the elements of W.
Asymptotic results for the stochastic processes of the personal inclinations Z^j = (Z_{n,j})_n have
been subject of studies in recent papers (e.g. [2, 21]); while the asymptotic behavior of the stochastic
processes of the actions (X_{n,j})_n has never been studied yet. In this paper, we fill this gap by characterizing the asymptotic behavior of the empirical means N_{n,j} = \sum_{k=1}^n X_{k,j} /n, proving their almost sure synchronization and some central limit theorems in the sense of stable convergence. Moreover, we discuss some statistical applications of these convergence results concerning confidence intervals for the random limit toward which all the processes of the system converge and tools to
make inference on the matrix W
Network reconstruction via density sampling
No full textReconstructing weighted networks from partial information is necessary in many important circumstances, e.g. for a correct estimation of systemic risk. It has been shown that, in order to achieve an accurate reconstruction, it is crucial to reliably replicate the empirical degree sequence, which is however unknown in many realistic situations. More recently, it has been found that the knowledge of the degree sequence can be replaced by the knowledge of the strength sequence, which is typically accessible, complemented by that of the total number of links, thus considerably relaxing the observational requirements. Here we further relax these requirements and devise a procedure valid when even the the total number of links is unavailable. We assume that, apart from the heterogeneity induced by the degree sequence itself, the network is homogeneous, so that its (global) link density can be estimated by sampling subsets of nodes with representative density. We show that the best way of sampling nodes is the random selection scheme, any other procedure being biased towards unrealistically large, or small, link densities. We then introduce our core technique for reconstructing both the topology and the link weights of the unknown network in detail. When tested on real economic and financial data sets, our method achieves a remarkable accuracy and is very robust with respect to the sampled subsets, thus representing a reliable practical tool whenever the available topological information is restricted to small portions of nodes
Global Value Chains Participation and Productivity Gains for North African Firms
No full textThe emergence of global value chains (GVCs) has provided some firms the opportunity to internationalize by specializing in the production of specific inputs or tasks along the chain, with a direct impact on a country’s competitiveness. China, for instance, managed to enter low value added phases in GVCs to rapidly become a major player in world trade. Against this background, this paper asks whether North Africa, given its favourable geographic position in the Mediterranean and proximity to Europe, can grab similar opportunities. In particular, it analyzes the GVCs participation of North African firms and its implications for productivity. Since the coordination of vertically fragmented production processes increasingly relies on an adequate level of quality and reliability, especially when the inputs from several stages and locations must come together in a specific way, we identify firms involved in GVCs as traders with internationally recognized quality certification. Using a propensity score matching diff-in-diff method, the paper finds that firms that enter GVCs both perform better ex ante and show additional productivity gains ex post. Results suggest that policies designed to support certifications and compliance with international standards and to increase trust between firms in different countries, represent an important tool for linking developing countries to global production networks, with possible positive consequences on their economic development and growth
Nuove sinergie per la gestione museale
No full textThe article analyses the essential cooperation of public bodies and private operators for the management of museums in different juridical contexts. Moving from the actual legal and institutional environment, the author introduces a comparison between the Italian and British management models in order to recommend an evolution in the national museum management perspective. The analysis is developed through the study of practical cases, such as the comparison between the National Gallery in London and La Galleria Nazionale in Rome which clearly describes the distance between the two national institutional systems and their approach to private bodies. Moreover, thanks to the example offered by the Community Foundations instrument, the article means to express a serious need for Italian museums to be considered and regulated as a common good which asks the whole national community for a firm cooperation
Multi-parametric sensitivity analysis of the band structure for tetrachiral acoustic metamaterials
No full textTetrachiral materials are characterized by a cellular microstructure made by a periodic pattern of stiff rings and flexible ligaments. Their mechanical behaviour can be described by a planar lattice of rigid massive bodies and elastic massless beams. The periodic cell dynamics is governed by a monoatomic structural model, conveniently reduced to the only active degrees-of-freedom. The paper presents an explicit parametric description of the band structure governing the free propagation of elastic waves. By virtue of multiparametric perturbation techniques, sensitivity analyses are performed to achieve an analytical asymptotic approximation of the dispersion functions. The parametric conditions for the existence of full band gaps in the low-frequency range are established. Furthermore, the band gap amplitude is analytically assessed in the admissible parameter range. In tetrachiral acoustic metamaterials, stop bands can be opened by the introduction of intra-ring resonators. Perturbation methods can efficiently deal with the consequent enlargement of the mechanical parameter space. Indeed high-accuracy parametric approximations are achieved for the band structure, enriched by the new optical branches related to the resonator frequencies. In particular, target stop bands in the metamaterial spectrum are analytically designed through the asymptotic solution of inverse spectral problems
"Il nastro dei sogni"? Il diritto (pubblico) del cinema e dell'audiovisivo
No full textThe article examines the new Italian regulation of cinema and audio-visual designed by Act No. 220/2016. The first part illustrates the main features of the new system, which has been implemented by over 20 decrees adopted during the last 12 months. Changes are numerous and regard several issues, such as financial resources, tax incentives, extraordinary measures, and the institutional asset. The second part focuses on the three legislative decrees adopted in December 2017, which completed the reform process. These decrees have significantly innovated the field of protection of minors, jobs regulation, and promotion of European and Italian audio-visual works. The reform, therefore, draws an ambitious design, which can offer an important contribution to the development of a dedicated field of study and research, the public law of cinema and audio-visual
Collective Memories, Propaganda and Authoritarian Political Support
Full text linkTo what extent does the degree of authoritarian political support depend on collective memories of a past experience with democracy? And how costly is it for a dictator to manipulate such memories with the help of propaganda? In this paper, we develop a political economy model with endogenous reference points, where a dictator strategically recalls traumatic collective memories of past political instability with the help of propaganda, to convince the population that an autocratic status quo is superior to a potential democratic alternative. In our
model, both the optimal level of propaganda and collective memories are jointly determined. We show how the marginal benefit of propaganda is positively correlated both with the amount of rent distribution within the elite, and the intensity of a past traumatic experience with democracy. We illustrate our theoretical findings
with case-studies of two authoritarian regimes that were preceded by periods of political instability—the Russian Federation under Vladimir Putin, and Chile under Augusto Pinochet. We then also provide cross-country empirical evidence in support of our argument
Smart Contract Negotiation in Cloud Computing
No full textA smart contract is the formalisation of an agreement, whose terms are automatically enforced by relying on a transaction protocol, while minimising the need of intermediaries. Such contracts not only specify the service and its quality but also the possible changes at runtime of the terms of agreement. Although smart contracts provide a great deal of flexibility, analysing their compatibility and reaching agreements with this level of dynamism is considerably more challenging, due to the freedom of clients and providers in formulating needs/offers. We introduce a formal language to specify interactions between offers and requests and present a methodology for the autonomous negotiation of smart contracts, which analyses the cost and the necessary changes for reaching an agreement. Moreover, we describe a set of experiments that provides insights on the relative cost of dynamism in negotiating smart contracts and compare the request/offer matching rates of our solution with related works
Synchronization of phase oscillators on the hierarchical lattice
No full textSynchronization of neurons forming a network with a hierarchical structure is essential for the brain to be able to function optimally. In this paper we study synchronization of phase oscillators on the most basic example of such a network, namely, the hierarchical lattice. Each oscillator has a natural frequency, drawn independently from a common probability distribution. In addition, pairs of oscillators interact with each other at a strength that depends on their hierarchical distance, modulated by a sequence of interaction parameters. We look at block averages of the oscillators on successive hierarchical scales, which we think of as block communities. Also these block communities are given a natural frequency, drawn independently from a common probability distribution that depends on their hierarchical scale. In the limit as the number of oscillators per community tends to infinity, referred to as the hierarchical mean-field limit, we find a separation of time scales, i.e., each block community behaves like a single oscillator evolving on its own time scale. We show that the evolution of the block communities is given by a renormalized mean-field noisy Kuramoto equation, with a synchronization level that depends on the hierarchical scale of the block community. We identify three universality classes for the synchronization levels on successive hierarchical scales, with explicit characterizations in terms of the sequence of interaction parameters and the sequence of natural frequency probability distributions. We show that disorder reduces synchronization when the natural frequency probability distributions are symmetric and unimodal, with the reduction gradually vanishing as the hierarchical scale goes up