Journal articles: 'Diffusion cascades'

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Han, Jinyoung, Daejin Choi, Jungseock Joo, and Chen-Nee Chuah. "Predicting Popular and Viral Image Cascades in Pinterest." Proceedings of the International AAAI Conference on Web and Social Media 11, no. 1 (May 3, 2017): 82–91. http://dx.doi.org/10.1609/icwsm.v11i1.14879.

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The word-of-mouth diffusion has been regarded as an important mechanism to advertise a new idea, image, technology, or product in online social networks (OSNs). This paper studies the prediction of popular and viral image diffusion in Pinterest. We first characterize an image cascade from two perspectives: (i) volume — how large the cascade is, that is, total number of users reached, and (ii) structural virality — how many users in the cascade are responsible for attracting other users. Our model predicts whether an image will be (a) popular in terms of the volume of its cascade, or (b) viral in terms of the structural virality. Our analysis reveals that a popular image is not necessarily viral, and vice versa. This motivates us to investigate whether there are distinctive features for accurately predicting popular or viral image cascades. To predict the popular or viral image cascades, we consider the following feature sets: (i) deep image features, (ii) image meta and poster's information, and (iii) initial propagation pattern. We find that using deep image features alone is not as effective in predicting popular or viral image cascades. We show that image meta and poster's information are strong predictors for predicting popular image cascades while image meta and initial propagation patterns are useful to predict viral image cascades. We believe our exploration can give an important insight for content providers, OSN operators, and marketers in predicting popular or viral image diffusion.

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Sharma, Karishma, Xinran He, Sungyong Seo, and Yan Liu. "Network Inference from a Mixture of Diffusion Models for Fake News Mitigation." Proceedings of the International AAAI Conference on Web and Social Media 15 (May 22, 2021): 668–79. http://dx.doi.org/10.1609/icwsm.v15i1.18093.

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The dissemination of fake news intended to deceive people, influence public opinion and manipulate social outcomes, has become a pressing problem on social media. Moreover, information sharing on social media facilitates diffusion of viral information cascades. In this work, we focus on understanding and leveraging diffusion dynamics of false and legitimate contents in order to facilitate network interventions for fake news mitigation. We analyze real-world Twitter datasets comprising fake and true news cascades, to understand differences in diffusion dynamics and user behaviours with regards to fake and true contents. Based on the analysis, we model the diffusion as a mixture of Independent Cascade models (MIC) with parameters \theta_T , \theta_F over the social network graph; and derive unsupervised inference techniques for parameter estimation of the diffusion mixture model from observed, unlabeled cascades. Users influential in the propagation of true and fake contents are identified using the inferred diffusion dynamics. Characteristics of the identified influential users reveal positive correlation between influential users identified for fake news and their relative appearance in fake news cascades. Identified influential users tend to be related to topics of more viral information cascades than less viral ones; and identified fake news influential users have relatively fewer counts of direct followers, compared to the true news influential users. Intervention analysis on nodes and edges demonstrates capacity of the inferred diffusion dynamics in supporting network interventions for mitigation.

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BALMFORTH, N. J., and W. R. YOUNG. "Diffusion-limited scalar cascades." Journal of Fluid Mechanics 482 (May 10, 2003): 91–100. http://dx.doi.org/10.1017/s0022112003003914.

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Sun, Ling, Yuan Rao, Xiangbo Zhang, Yuqian Lan, and Shuanghe Yu. "MS-HGAT: Memory-Enhanced Sequential Hypergraph Attention Network for Information Diffusion Prediction." Proceedings of the AAAI Conference on Artificial Intelligence 36, no. 4 (June 28, 2022): 4156–64. http://dx.doi.org/10.1609/aaai.v36i4.20334.

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Predicting the diffusion cascades is a critical task to understand information spread on social networks. Previous methods usually focus on the order or structure of the infected users in a single cascade, thus ignoring the global dependencies of users and cascades, limiting the performance of prediction. Current strategies to introduce social networks only learn the social homogeneity among users, which is not enough to describe their interaction preferences, let alone the dynamic changes. To address the above issues, we propose a novel information diffusion prediction model named Memory-enhanced Sequential Hypergraph Attention Networks (MS-HGAT). Specifically, to introduce the global dependencies of users, we not only take advantages of their friendships, but also consider their interactions at the cascade level. Furthermore, to dynamically capture user' preferences, we divide the diffusion hypergraph into several sub graphs based on timestamps, develop Hypergraph Attention Networks to learn the sequential hypergraphs, and connect them with gated fusion strategy. In addition, a memory-enhanced embedding lookup module is proposed to capture the learned user representations into the cascade-specific embedding space, thus highlighting the feature interaction within the cascade. The experimental results over four realistic datasets demonstrate that MS-HGAT significantly outperforms the state-of-the-art diffusion prediction models in both Hits@K and MAP@k metrics.

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Hellmann, M., D. W. Heermann, and M. Weiss. "Enhancing phosphorylation cascades by anomalous diffusion." EPL (Europhysics Letters) 97, no. 5 (February 22, 2012): 58004. http://dx.doi.org/10.1209/0295-5075/97/58004.

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White, D. A. "Gas diffusion cascades—properties and optimization." Chemical Engineering Science 45, no. 6 (1990): 1567–70. http://dx.doi.org/10.1016/0009-2509(90)80008-3.

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Huang, Ningbo, Gang Zhou, Mengli Zhang, Meng Zhang, and Ze Yu. "Modelling the Latent Semantics of Diffusion Sources in Information Cascade Prediction." Computational Intelligence and Neuroscience 2021 (September 29, 2021): 1–12. http://dx.doi.org/10.1155/2021/7880215.

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Predicting the information spread tendency can help products recommendation and public opinion management. The existing information cascade prediction models are devoted to extract the chronological features from diffusion sequences but treat the diffusion sources as ordinary users. Diffusion source, the first user in the information cascade, can indicate the latent topic and diffusion pattern of an information item to mine user potential common interests, which facilitates information cascade prediction. In this paper, for modelling the abundant implicit semantics of diffusion sources in information cascade prediction, we propose a Diffusion Source latent Semantics-Fused cascade prediction framework, named DSSF. Specifically, we firstly apply diffusion sources embedding to model the special role of the source users. To learn the latent interaction between users and diffusion sources, we proposed a co-attention-based fusion gate which fuses the diffusion sources’ latent semantics with user embedding. To address the challenge that the distribution of diffusion sources is long-tailed, we develop an adversarial training framework to transfer the semantics knowledge from head to tail sources. Finally, we conduct experiments on real-world datasets, and the results show that modelling the diffusion sources can significantly improve the prediction performance. Besides, this improvement is limited for the cascades from tail sources, and the adversarial framework can help.

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Van Rossum, M., and Y. T. Cheng. "Diffusion in Collision Cascades: a Thermodynamic Viewpoint." Defect and Diffusion Forum 57-58 (January 1988): 1–32. http://dx.doi.org/10.4028/www.scientific.net/ddf.57-58.1.

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Rossi, Francois, and N. V. Doan. "Nonlinear effects of diffusion in displacement cascades." Nuclear Instruments and Methods in Physics Research Section B: Beam Interactions with Materials and Atoms 61, no. 1 (July 1991): 27–37. http://dx.doi.org/10.1016/0168-583x(91)95556-s.

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SMITH, K. S., G. BOCCALETTI, C. C. HENNING, I. MARINOV, C. Y. TAM, I. M. HELD, and G. K. VALLIS. "Turbulent diffusion in the geostrophic inverse cascade." Journal of Fluid Mechanics 469 (October 15, 2002): 13–48. http://dx.doi.org/10.1017/s0022112002001763.

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Motivated in part by the problem of large-scale lateral turbulent heat transport in the Earth's atmosphere and oceans, and in part by the problem of turbulent transport itself, we seek to better understand the transport of a passive tracer advected by various types of fully developed two-dimensional turbulence. The types of turbulence considered correspond to various relationships between the streamfunction and the advected field. Each type of turbulence considered possesses two quadratic invariants and each can develop an inverse cascade. These cascades can be modified or halted, for example, by friction, a background vorticity gradient or a mean temperature gradient. We focus on three physically realizable cases: classical two-dimensional turbulence, surface quasi-geostrophic turbulence, and shallow-water quasi-geostrophic turbulence at scales large compared to the radius of deformation. In each model we assume that tracer variance is maintained by a large-scale mean tracer gradient while turbulent energy is produced at small scales via random forcing, and dissipated by linear drag. We predict the spectral shapes, eddy scales and equilibrated energies resulting from the inverse cascades, and use the expected velocity and length scales to predict integrated tracer fluxes.When linear drag halts the cascade, the resulting diffusivities are decreasing functions of the drag coefficient, but with different dependences for each case. When β is significant, we find a clear distinction between the tracer mixing scale, which depends on β but is nearly independent of drag, and the energy-containing (or jet) scale, set by a combination of the drag coefficient and β. Our predictions are tested via high- resolution spectral simulations. We find in all cases that the passive scalar is diffused down-gradient with a diffusion coefficient that is well-predicted from estimates of mixing length and velocity scale obtained from turbulence phenomenology.

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BRAHIM, ABDELHAMID SALAH, BÉNÉDICTE LE GRAND, and MATTHIEU LATAPY. "DIFFUSION CASCADES: SPREADING PHENOMENA IN BLOG NETWORK COMMUNITIES." Parallel Processing Letters 22, no. 01 (March 2012): 1240002. http://dx.doi.org/10.1142/s0129626412400026.

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A diffusion cascade occurs when information spreads from one node to the rest of the network through a succession of diffusion events. So far diffusion phenomena have been mostly considered at a macroscopic scale i.e. by studying all nodes of the network. We give a complementary way to analyse network interactions by considering the problem at different scales. To that purpose, we use the community structure of the network to characterize diffusion between nodes (and between communities) and to identify interactions behaviour patterns.

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Sadler, Evan. "Diffusion Games." American Economic Review 110, no. 1 (January 1, 2020): 225–70. http://dx.doi.org/10.1257/aer.20180601.

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Behaviors and information often spread via person-to-person diffusion. This paper highlights how diffusion processes can facilitate coordination. I study contagion in a discrete network with Bayesian players. In addition to characterizing the extent and rate of adoption, we uncover a new effect: when large cascades are possible in equilibrium, exposure conveys information about a player’s network position. This effect underscores a novel trade-off in the design of marketing campaigns, suggesting conditions under which word-of-mouth is relatively more effective. A generalization of the model to multi-type networks suggests a new approach to targeted seeding. (JEL D83, D85, M31, M37, Z13)

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Liu, Bo, Qidong Chen, Jun Li, and Xiaochen Mao. "Novel Optimization Design Methods of Highly Loaded Compressor Cascades Considering Endwall Effect." Entropy 24, no. 6 (June 15, 2022): 830. http://dx.doi.org/10.3390/e24060830.

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The endwall effect has a great impact on the aerodynamic performance of compressor blades. Based on three conventional near-endwall blade modeling methods of bowed blade, endbend blade and leading-edge strake blade (LESB), two combined optimization design methods of highly loaded blades have been developed considering the endwall effect in the current study, i.e., the bowed blade combined with the LESB (bowed LESB blade) and the endbend blade combined with the LESB (endbend LESB blade). Optimization designs were conducted for a compressor cascade with low solidity by using the two combined modeling methods and the three conventional modeling methods, and the optimization results were compared and analyzed in detail. The results showed that the five optimization modelling methods could all improve the performance for the original cascade, and the optimized cascade with the bowed LESB modeling method has the best aerodynamic performance. The total pressure loss of the optimal bowed LESB cascade was only 40.3% of that in the original cascade while reducing the solidity of the original cascade from 1.53 to 1.25 and keeping the static pressure rise and diffusion factor at the same level as the original one. Among the optimal cascades, the radial migration height of the low-energy fluid and the corresponding vortex have great effects on the aerodynamic performance, and the optimal bowed LESB cascade is superior to the other optimal cascades in this aspect.

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Kim, Joohyun, Ohsung Kwon, and Duk Hee Lee. "Social influence of hubs in information cascade processes." Management Decision 55, no. 4 (May 15, 2017): 730–44. http://dx.doi.org/10.1108/md-10-2016-0681.

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Purpose The purpose of this paper is to explore how hubs’ social influence on social network decisions can cause the behavior of information cascades in a market. Design/methodology/approach The authors establish understanding of the fundamental mechanism of information cascades through a computational simulation approach. Findings Eigenvector centrality, betweenness centrality, and PageRank are statistically correlated with the occurrence of information cascades among agents; the hubs’ incorrect decisions in the early diffusion stage can significantly cause misled shift cascades; and the bridge role of hubs is more influential than their pivotal position role in the process of misled shift cascades. Originality/value This implication can be extendable in the field of marketing, sequential voting, and technology, or innovation adoption.

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Huang, Song, Chengwu Yang, Ge Han, Shengfeng Zhao, and Xingen Lu. "Multipoint design optimization for a controlled diffusion airfoil compressor cascade." Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science 234, no. 11 (February 10, 2020): 2143–59. http://dx.doi.org/10.1177/0954406220904730.

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Under high altitude and low Reynolds number conditions, the aerodynamic performance of compressor cascades deteriorates drastically. In this paper, an optimally designed system combining class-shape-transformation method, S1 surface flow solver and whale optimization algorithm was established to achieve for a controlled diffusion airfoil, called MANGHH. The aim of this work is to improve our understanding of the loss mechanism for the original cascade and optimal cascade under different inflow conditions. The study shows that the total pressure loss of the optimal cascade at an angle of attack of −4°, 0°, and 6° decreases by 55.9%, 16.1%, and 16.3%, respectively, compared with the original controlled diffusion airfoil. The range of the available low loss incidence improves significantly. At different incidences, the optimal cascade moves the blade loading forward compared with that of the original controlled diffusion airfoil while reducing the growth rate of the boundary layer thickness, eliminating a wide range of flow separations. The optimal cascade reduces the total pressure loss mainly by reducing trailing edge mixing loss compared with that of the original controlled diffusion airfoil. Under different inlet Mach number conditions, a laminar separation bubble appears on the suction surface of the original controlled diffusion airfoil. As the inlet Mach number increases, the position of the laminar separation bubble moves slightly upstream, while the length and depth of the laminar separation bubble increase. Fortunately, the total pressure loss of the optimal cascade decreases significantly compared with that of the original controlled diffusion airfoil. Under different incoming turbulence intensity conditions, the total pressure loss of the optimal cascade is always lower than that of the original controlled diffusion airfoil. As the incoming turbulence intensity increases, the total pressure loss of the original controlled diffusion airfoil decreases first and then increases. However, the total pressure loss of the optimal cascade increases with increasing incoming turbulence intensity due to the improvement of the turbulence dissipation capacity.

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Rechter, H., W. Steinert, and K. Lehmann. "Comparison of Controlled Diffusion Airfoils With Conventional NACA 65 Airfoils Developed for Stator Blade Application in a Multistage Axial Compressor." Journal of Engineering for Gas Turbines and Power 107, no. 2 (April 1, 1985): 494–98. http://dx.doi.org/10.1115/1.3239758.

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In their transonic cascade wind tunnel, DFVLR has done measurements on a conventional NACA 65, as well as on a controlled diffusion airfoil, designed for the same velocity triangle at supercritical inlet condition. These tested cascades represent the first stator hub section of a three-stage axial/one-stage radial combined compressor developed by MTU with the financial aid of the German Ministry of Research and Technology. One aspect of this project was the verification of the controlled diffusion concept for axial compressor blade design, in order to demonstrate the capabilities of some recent research results which are now available for industrial application. The stator blades of the axial compressor section were first designed using NACA 65 airfoils. In the second step, the controlled diffusion technique was applied for building a new stator set. Both stator configurations were tested in the MTU compressor test facility. Cascade and compressor tests revealed the superiority of the controlled diffusion airfoils for axial compressors. In comparison to the conventional NACA blades, the new blades obtained a higher efficiency. Furthermore, a closer matching of the compressor performance data to the design requirements was possible due to a more precise prediction of the turning angle.

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Rabb, Nicholas, Lenore Cowen, Jan P. de Ruiter, and Matthias Scheutz. "Cognitive cascades: How to model (and potentially counter) the spread of fake news." PLOS ONE 17, no. 1 (January 7, 2022): e0261811. http://dx.doi.org/10.1371/journal.pone.0261811.

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Understanding the spread of false or dangerous beliefs—often called misinformation or disinformation—through a population has never seemed so urgent. Network science researchers have often taken a page from epidemiologists, and modeled the spread of false beliefs as similar to how a disease spreads through a social network. However, absent from those disease-inspired models is an internal model of an individual’s set of current beliefs, where cognitive science has increasingly documented how the interaction between mental models and incoming messages seems to be crucially important for their adoption or rejection. Some computational social science modelers analyze agent-based models where individuals do have simulated cognition, but they often lack the strengths of network science, namely in empirically-driven network structures. We introduce a cognitive cascade model that combines a network science belief cascade approach with an internal cognitive model of the individual agents as in opinion diffusion models as a public opinion diffusion (POD) model, adding media institutions as agents which begin opinion cascades. We show that the model, even with a very simplistic belief function to capture cognitive effects cited in disinformation study (dissonance and exposure), adds expressive power over existing cascade models. We conduct an analysis of the cognitive cascade model with our simple cognitive function across various graph topologies and institutional messaging patterns. We argue from our results that population-level aggregate outcomes of the model qualitatively match what has been reported in COVID-related public opinion polls, and that the model dynamics lend insights as to how to address the spread of problematic beliefs. The overall model sets up a framework with which social science misinformation researchers and computational opinion diffusion modelers can join forces to understand, and hopefully learn how to best counter, the spread of disinformation and “alternative facts.”

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Woo, C. H., B. N. Singh, and H. Heinisch. "A diffusion approach to modelling of irradiation-induced cascades." Journal of Nuclear Materials 174, no. 2-3 (November 1990): 190–95. http://dx.doi.org/10.1016/0022-3115(90)90233-d.

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Le Saux, Thomas, Raphaël Plasson, and Ludovic Jullien. "Energy propagation throughout chemical networks." Chem. Commun. 50, no. 47 (2014): 6189–95. http://dx.doi.org/10.1039/c4cc00392f.

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Kinoshita, Hisao, N. Sakaguch, S. Watanabe, H. Takahashil, Masayoshi Kawai, Rolf Gotthardt, and F. Phillipp. "Formation of Al-Based Intermetallic Compound under Ion Implantation at Lower Temperature." Materials Science Forum 561-565 (October 2007): 1729–32. http://dx.doi.org/10.4028/www.scientific.net/msf.561-565.1729.

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The formation process of intermetallic compound under Ni+ion implantation into pure Al was studied at lower temperature below room temperature. Ion implantation was carried out using 250KeV ion accelerator. Cascade damage was introduced Ni+ions implantation at 223K without new phase nucleation. However, when Ni+ions were implanted at room temperature, the grown larger plate-like phases were observed during implantation up to 1x1017 Ni+/cm2. Ni concentration in Al matrix and newly formed phase were 0.3-0.5 and 8.5-13.3at%,respectively. It was identified that the formed phases were close to the ordered orthorhombic structure of Al3Ni type. It was also confirmed from observation with high resolution HVEM that these phases grew with continuous ion implantation. Thus it was clarified that cascades act as preferential nucleation site for intermetallic compound, and the phases nucleated at cascades coalesce in the growth process of each phase during continuous implantation through ion irradiation enhanced diffusion.

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Sun, Eric, Itamar Rosenn, Cameron Marlow, and Thomas Lento. "Gesundheit! Modeling Contagion through Facebook News Feed." Proceedings of the International AAAI Conference on Web and Social Media 3, no. 1 (March 19, 2009): 146–53. http://dx.doi.org/10.1609/icwsm.v3i1.13947.

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Whether they are modeling bookmarking behavior in Flickr or cascades of failure in large networks, models of diffusion often start with the assumption that a few nodes start long chain reactions, resulting in large-scale cascades. While reasonable under some conditions, this assumption may not hold for social media networks, where user engagement is high and information may enter a system from multiple disconnected sources. Using a dataset of 262,985 Facebook Pages and their associated fans, this paper provides an empirical investigation of diffusion through a large social media network. Although Facebook diffusion chains are often extremely long (chains of up to 82 levels have been observed), they are not usually the result of a single chain-reaction event. Rather, these diffusion chains are typically started by a substantial number of users. Large clusters emerge when hundreds or even thousands of short diffusion chains merge together. This paper presents an analysis of these diffusion chains using zero-inflated negative binomial regressions. We show that after controlling for distribution effects, there is no meaningful evidence that a start node’s maximum diffusion chain length can be predicted with the user's demographics or Facebook usage characteristics (including the user's number of Facebook friends). This may provide insight into future research on public opinion formation.

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Anh, Nguyen Viet, Duong Ngoc Son, Nguyen Thi Thu Ha, Sergey Kuznetsov, and Nguyen Tran Quoc Vinh. "A method for determining information diffusion cascades on social networks." Eastern-European Journal of Enterprise Technologies 6, no. 2 (96) (December 10, 2018): 61–69. http://dx.doi.org/10.15587/1729-4061.2018.150295.

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Berezhkovskii, A. M., M. Coppey, and S. Y. Shvartsman. "Signaling gradients in cascades of two-state reaction-diffusion systems." Proceedings of the National Academy of Sciences 106, no. 4 (January 15, 2009): 1087–92. http://dx.doi.org/10.1073/pnas.0811807106.

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Belák, Václav, Afra Mashhadi, Alessandra Sala, and Donn Morrison. "Phantom cascades: The effect of hidden nodes on information diffusion." Computer Communications 73 (January 2016): 12–21. http://dx.doi.org/10.1016/j.comcom.2015.07.012.

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Xia, Yan, Ted Hsuan Yun Chen, and Mikko Kivelä. "Limits of Multilayer Diffusion Network Inference in Social Media Research." Proceedings of the International AAAI Conference on Web and Social Media 16 (May 31, 2022): 1145–56. http://dx.doi.org/10.1609/icwsm.v16i1.19365.

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Information on social media spreads through an underlying diffusion network that connects people of common interests and opinions. This diffusion network often comprises multiple layers, each capturing the spreading dynamics of a certain type of information characterized by, for example, topic, language, or attitude. Researchers have previously proposed methods to infer these underlying multilayer diffusion networks from observed spreading patterns, but little is known about how well these methods perform across the range of realistic spreading data. In this paper, we conduct an extensive series of synthetic data experiments to systematically analyze the performance of the multilayer diffusion network inference framework, under varied network structure (e.g. density, number of layers) and information diffusion settings (e.g. cascade size, layer mixing) that are designed to mimic real-world spreading on social media. Our results show extreme performance variation of the inference framework: notably, it achieves much higher accuracy when inferring a denser diffusion network, while it fails to decompose the diffusion network correctly when most cascades in the data reach a limited audience. In demonstrating the conditions under which the inference accuracy is extremely low, our paper highlights the need to carefully evaluate the applicability of the inference before running it on real data. Practically, our results serve as a reference for this evaluation, and our publicly available implementation, which outperforms previous implementations in accuracy, supports further testing under personalized settings.

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Soboleva, Olga N., and Ekaterina P. Kurochkina. "Subgrid modelling of convective diffusion in a multiscale random medium." Russian Journal of Numerical Analysis and Mathematical Modelling 34, no. 3 (June 26, 2019): 151–62. http://dx.doi.org/10.1515/rnam-2019-0013.

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Abstract Effective coefficients for convective diffusion equations are obtained. Correlated random fields of conductivity and porosity are approximated by multiplicative cascades with log-normal distributions of probabilities. The theoretical result is checked numerically for the case of 3D plane flow of an incompressible fluid.

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Panagopoulos, George, Fragkiskos D. Malliaros, and Michalis Vazirgianis. "Influence Maximization Using Influence and Susceptibility Embeddings." Proceedings of the International AAAI Conference on Web and Social Media 14 (May 26, 2020): 511–21. http://dx.doi.org/10.1609/icwsm.v14i1.7319.

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Finding a set of users that can maximize the spread of information in a social network is an important problem in social media analysis — being a critical part of several real-world applications such as viral marketing, political advertising and epidemiology. Although influence maximization has been studied extensively in the past, the majority of works focus on the algorithmic aspect of the problem, overlooking several practical improvements that can be derived by data-driven observations or the inclusion of machine learning. The main challenges of realistic influence maximization is on the one hand the computational demand of the diffusion models' repetitive simulations, and on the other the accuracy of the estimated influence spread. In this work, we propose Celfie, an influence maximization method that utilizes learnt influence representations from diffusion cascades to overcome the use of diffusion models. It comprises of two parts. The first is based on Inf2vec, an unsupervised learning model that embeds influence relationships between nodes from a set of diffusion cascades. We create a new version of the model, based on observations from influence analysis on a large scale dataset, to match the scalability needs and the purpose of influence maximization. The second part capitalizes on the learned representations to redefine the traditional live-edge model sampling for the computation of the marginal gain. For evaluation, we apply our method in the Sina Weibo and Microsoft Academic Graph datasets, two large scale networks accompanied by diffusion cascades. We observe that our algorithm outperforms various baseline methods in terms of seed set quality and speed. In addition, the proposed Inf2vec modification for influence maximization provides substantial computational advantages in the price of a minuscule loss in the influence spread.

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Dow, P. Alex, Lada Adamic, and Adrien Friggeri. "The Anatomy of Large Facebook Cascades." Proceedings of the International AAAI Conference on Web and Social Media 7, no. 1 (August 3, 2021): 145–54. http://dx.doi.org/10.1609/icwsm.v7i1.14431.

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When users post photos on Facebook, they have the option of allowing their friends, followers, or anyone at all to subsequently reshare the photo. A portion of the billions of photos posted to Facebook generates cascades of reshares, enabling many additional users to see, like, comment, and reshare the photos. In this paper we present characteristics of such cascades in aggregate, finding that a small fraction of photos account for a significant proportion of reshare activity and generate cascades of non-trivial size and depth. We also show that the true influence chains in such cascades can be much deeper than what is visible through direct attribution. To illuminate how large cascades can form, we study the diffusion trees of two widely distributed photos: one posted on President Barack Obama’s page following his reelection victory, and another posted by an individual Facebook user hoping to garner enough likes for a cause. We show that the two cascades, despite achieving comparable total sizes, are markedly different in their time evolution, reshare depth distribution, predictability of subcascade sizes, and the demographics of users who propagate them. The findings suggest not only that cascades can achieve considerable size but that they can do so in distinct ways.

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Connaughton, C., and R. McAdams. "Mixed flux-equipartition solutions of a diffusion model of nonlinear cascades." EPL (Europhysics Letters) 95, no. 2 (July 1, 2011): 24005. http://dx.doi.org/10.1209/0295-5075/95/24005.

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Tump, Alan N., Timothy J. Pleskac, and Ralf H. J. M. Kurvers. "Wise or mad crowds? The cognitive mechanisms underlying information cascades." Science Advances 6, no. 29 (July 2020): eabb0266. http://dx.doi.org/10.1126/sciadv.abb0266.

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Whether getting vaccinated, buying stocks, or crossing streets, people rarely make decisions alone. Rather, multiple people decide sequentially, setting the stage for information cascades whereby early-deciding individuals can influence others’ choices. To understand how information cascades through social systems, it is essential to capture the dynamics of the decision-making process. We introduce the social drift–diffusion model to capture these dynamics. We tested our model using a sequential choice task. The model was able to recover the dynamics of the social decision-making process, accurately capturing how individuals integrate personal and social information dynamically over time and when their decisions were timed. Our results show the importance of the interrelationships between accuracy, confidence, and response time in shaping the quality of information cascades. The model reveals the importance of capturing the dynamics of decision processes to understand how information cascades in social systems, paving the way for applications in other social systems.

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Park, Byungwoo, and Hyukjae Lee. "Ion-beam mixing in energetic collision cascades: Thermal-spike model and experiments." Journal of Materials Research 14, no. 1 (January 1999): 281–85. http://dx.doi.org/10.1557/jmr.1999.0040.

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A phenomenological model of ion-beam mixing during energetic collision cascades is developed, based on the concept of a thermal spike, to correctly predict that the mixing rate Dt depends linearly on nuclear stopping power (instead of a power-law dependence), and is correlated with a heat of mixing (analogous to Darken's relation). Previous ion-beam mixing experiments from 25 different metallic bilayers agree well with the model's predictions: mixing rates (Dt)/(ion-dose) ∼ 1 nm4, and an activation enthalpy of approximately 1 eV for atomic diffusion in liquid-like cascades.

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Cao, Zhiyuan, Bo Liu, and Ting Zhang. "Control of separations in a highly loaded diffusion cascade by tailored boundary layer suction." Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science 228, no. 8 (October 10, 2013): 1363–74. http://dx.doi.org/10.1177/0954406213508281.

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In order to explore the control mechanism of boundary layer suction on the separated flows of highly loaded diffusion cascades, a linear compressor cascade, which has separated flows on the whole span and three-dimensional separations over the suction surface/endwall corner, was investigated by tailored boundary layer suction. Three suction surface-slotted schemes and two combined suction surface/endwall-slotted schemes were designed. The original cascade and the cascade with part blade span suction were experimentally investigated on a high-subsonic cascade wind tunnel. In addition, numerical simulation was employed to study the flow fields of different suction schemes in detail. The results shows that while tailored boundary layer suction at part blade span can effectively remove the separations at the suction span, the flow fields of other spans deteriorated. The reasons are the ‘C’ shape or reverse ‘C’ shape spanwise distribution of static pressure after part blade span boundary layer suction. Suction surface boundary layer suction over the whole span can obviously eliminate the separation at the suction surface. However, because of the endwall boundary layer, suction surface boundary layer suction cannot effectively remove the corner three-dimensional separation. The separation over the whole span and the three-dimensional separation at the corner are completely eliminated by combined suction surface/endwall boundary layer suction. After combined boundary layer suction, the static pressure distribution over the blade span just like the shape of ‘C’ is good for the transport of the low-energy fluid near the endwall to the midspan.

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Kent, J., C. Jablonowski, J. P. Whitehead, and R. B. Rood. "Downscale cascades in tracer transport test cases: an intercomparison of the dynamical cores in the Community Atmosphere Model CAM5." Geoscientific Model Development 5, no. 6 (December 6, 2012): 1517–30. http://dx.doi.org/10.5194/gmd-5-1517-2012.

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Abstract. The accurate modeling of cascades to unresolved scales is an important part of the tracer transport component of dynamical cores of weather and climate models. This paper aims to investigate the ability of the advection schemes in the National Center for Atmospheric Research's Community Atmosphere Model version 5 (CAM5) to model this cascade. In order to quantify the effects of the different advection schemes in CAM5, four two-dimensional tracer transport test cases are presented. Three of the tests stretch the tracer below the scale of coarse resolution grids to ensure the downscale cascade of tracer variance. These results are compared with a high resolution reference solution, which is simulated on a resolution fine enough to resolve the tracer during the test. The fourth test has two separate flow cells, and is designed so that any tracer in the western hemisphere should not pass into the eastern hemisphere. This is to test whether the diffusion in transport schemes, often in the form of explicit hyper-diffusion terms or implicit through monotonic limiters, contains unphysical mixing. An intercomparison of three of the dynamical cores of the National Center for Atmospheric Research's Community Atmosphere Model version 5 is performed. The results show that the finite-volume (CAM-FV) and spectral element (CAM-SE) dynamical cores model the downscale cascade of tracer variance better than the semi-Lagrangian transport scheme of the Eulerian spectral transform core (CAM-EUL). Each scheme tested produces unphysical mass in the eastern hemisphere of the separate cells test.

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Kent, J., C. Jablonowski, J. P. Whitehead, and R. B. Rood. "Downscale cascades in tracer transport test cases: an intercomparison of the dynamical cores in the Community Atmosphere Model CAM5." Geoscientific Model Development Discussions 5, no. 3 (July 16, 2012): 1781–816. http://dx.doi.org/10.5194/gmdd-5-1781-2012.

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Abstract. The accurate modelling of cascades to unresolved scales is an important part of the tracer transport component of dynamical cores of weather and climate models. This paper aims to investigate the ability of the advection schemes in the National Center for Atmospheric Research's Community Atmosphere Model version 5 (CAM5) to model this cascade. In order to quantify the effects of the different advection schemes in CAM5, four two-dimensional tracer transport test cases are presented. Three of the tests stretch the tracer below the scale of coarse resolution grids to ensure the downscale cascade of tracer variance. These results are compared with a high resolution reference solution, which is simulated on a resolution fine enough to resolve the tracer during the test. The fourth test has two separate flow cells, and is designed so that any tracer in the Western Hemisphere should not pass into the Eastern Hemisphere. This is to test whether the diffusion in transport schemes, often in the form of explicit hyper-diffusion terms or implicit through monotonic limiters, contains unphysical mixing. An intercomparison of three of the dynamical cores of the National Center for Atmospheric Research's Community Atmosphere Model version 5 is performed. The results show that the finite-volume (CAM-FV) and spectral element (CAM-SE) dynamical cores model the downscale cascade of tracer variance better than the semi-Lagrangian transport scheme of the Eulerian spectral transform core (CAM-EUL). Each scheme tested produces unphysical mass in the Eastern Hemisphere of the separate cells test.

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Peng, Jun, Lifeng Zhang, and Jiping Guan. "Applications of a Moist Nonhydrostatic Formulation of the Spectral Energy Budget to Baroclinic Waves. Part I: The Lower-Stratospheric Energy Spectra." Journal of the Atmospheric Sciences 72, no. 5 (May 1, 2015): 2090–108. http://dx.doi.org/10.1175/jas-d-14-0306.1.

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Abstract The authors investigate the mesoscale dynamics that produce the lower-stratospheric energy spectra in idealized moist baroclinic waves, using the moist nonhydrostatic formulation of spectral energy budget of kinetic energy and available potential energy by J. Peng et al. The inclusion of moist processes energizes the lower-stratospheric mesoscale, helping to close the gap between observed and simulated energy spectra. In dry baroclinic waves, the lower-stratospheric mesoscale is mainly forced by weak downscale cascades of both horizontal kinetic energy (HKE) and available potential energy (APE) and by a weak conversion of APE to HKE. At wavelengths less than 1000 km, the pressure vertical flux divergence also has a significant positive contribution to the HKE; however, this positive contribution is largely counteracted by the negative HKE vertical flux divergence. In moist baroclinic waves, the lower-stratospheric mesoscale HKE is mainly generated by the pressure and HKE vertical flux divergences. This additional HKE is partly converted to APE and partly removed by diffusion. Another negative contribution to the mesoscale HKE is from the forcing of a visible upscale HKE cascade. Besides the conversion of HKE, however, the three-dimensional divergence also has a significant positive contribution to the mesoscale APE. With these two direct APE sources, the lower-stratospheric mesoscale also undergoes a much stronger upscale APE cascade. These results suggest that both downscale and upscale cascades through the mesoscale are permitted in the real atmosphere and the direct forcing of the mesoscale is available to feed the upscale energy cascade.

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Pacciani, R., M. Marconcini, A. Arnone, and F. Bertini. "An assessment of the laminar kinetic energy concept for the prediction of high-lift, low-Reynolds number cascade flows." Proceedings of the Institution of Mechanical Engineers, Part A: Journal of Power and Energy 225, no. 7 (November 2011): 995–1003. http://dx.doi.org/10.1177/0957650911412444.

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The laminar kinetic energy (LKE) concept has been applied to the prediction of low-Reynolds number flows, characterized by separation-induced transition, in high-lift airfoil cascades for aeronautical low-pressure turbine applications. The LKE transport equation has been coupled with the low-Reynolds number formulation of the Wilcox's k − ω turbulence model. The proposed methodology has been assessed against two high-lift cascade configurations, characterized by different loading distributions and suction-side diffusion rates, and tested over a wide range of Reynolds numbers. The aft-loaded T106C cascade is studied in both high- and low-speed conditions for several expansion ratios and inlet freestream turbulence values. The front-loaded T108 cascade is analysed in high-speed, low-freestream turbulence conditions. Numerical predictions with steady inflow conditions are compared to measurements carried out by the von Kármán Institute and the University of Cambridge. Results obtained with the proposed model show its ability to predict the evolution of the separated flow region, including bubble-bursting phenomenon and the formation of open separations, in high-lift, low-Reynolds number cascade flows.

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Del Vicario, Michela, Alessandro Bessi, Fabiana Zollo, Fabio Petroni, Antonio Scala, Guido Caldarelli, H. Eugene Stanley, and Walter Quattrociocchi. "The spreading of misinformation online." Proceedings of the National Academy of Sciences 113, no. 3 (January 4, 2016): 554–59. http://dx.doi.org/10.1073/pnas.1517441113.

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The wide availability of user-provided content in online social media facilitates the aggregation of people around common interests, worldviews, and narratives. However, the World Wide Web (WWW) also allows for the rapid dissemination of unsubstantiated rumors and conspiracy theories that often elicit rapid, large, but naive social responses such as the recent case of Jade Helm 15––where a simple military exercise turned out to be perceived as the beginning of a new civil war in the United States. In this work, we address the determinants governing misinformation spreading through a thorough quantitative analysis. In particular, we focus on how Facebook users consume information related to two distinct narratives: scientific and conspiracy news. We find that, although consumers of scientific and conspiracy stories present similar consumption patterns with respect to content, cascade dynamics differ. Selective exposure to content is the primary driver of content diffusion and generates the formation of homogeneous clusters, i.e., “echo chambers.” Indeed, homogeneity appears to be the primary driver for the diffusion of contents and each echo chamber has its own cascade dynamics. Finally, we introduce a data-driven percolation model mimicking rumor spreading and we show that homogeneity and polarization are the main determinants for predicting cascades’ size.

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Sturm, W., H. Scheugenpflug, and L. Fottner. "Performance Improvements of Compressor Cascades by Controlling the Profile and Sidewall Boundary Layers." Journal of Turbomachinery 114, no. 3 (July 1, 1992): 477–86. http://dx.doi.org/10.1115/1.2929168.

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For increasing the thrust-to-weight ratio of modern turbojet engines, the number of stages of the turbo components or at least the number of blades per stage must be minimized. This inevitably forces a higher loading of the remaining blades, for which, especially in the compressor, even the use of modern controlled diffusion airfoil concepts is limited due to the danger of flow separation. Therefore, boundary layer control can be taken into consideration. The use of blowing proves to be most obvious for applications in turbojet engines, because the required pressurized air is, due to the working process, already available. Basic investigations on this topic are described in this paper, and both the midspan and the sidewall region are covered. As a review of the pertinent literature disclosed the lack of reliable design criteria, fundamental experiments in a cascade wind tunnel were performed. The results of these measurements are reported and recommendations concerning the application of blowing in compressor cascades are given.

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Cao, Zhiyuan, Bo Liu, Ting Zhang, and Yibing Xu. "Design strategies and numerical simulation of highly loaded aspirated compressor blades." Proceedings of the Institution of Mechanical Engineers, Part A: Journal of Power and Energy 232, no. 4 (October 25, 2017): 315–36. http://dx.doi.org/10.1177/0957650917736921.

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Boundary layer suction can effectively eliminate flow separations and increase aerodynamic loading of axial compressors. The design methodology of highly loaded aspirated compressor blades was developed and illustrated in this study. In this work, Computational Fluid Dynamics (CFD) methods were first validated with existing data and then used to develop the design strategy of aspirated compressor blades. Design strategies for higher blade performances, including higher loading, larger stall margin and larger blade thickness near the suction slot of aspirated blades, were investigated through analyzing a series of highly loaded aspirated cascades with diffusion factors (DF) around 0.71. Results showed that the design methodology proposed in this paper was appropriate for designing highly loaded aspirated compressor blades. Under the condition of no boundary layer suction (BLS), severe flow separations of highly loaded blades were tailored at the aft part of suction surface by adopting the “ski-slope” velocity distribution, which almost remained unchanged within a large incidence range. The “ski-slope” velocity distribution was appropriate for removing flow separations and beneficial for obtaining thicker blade. High loading of aspirated blade was achieved by the postpositional suction peak and minimum velocity distribution on pressure surface. The stall margin of highly loaded aspirated cascades could be enlarged by designing the velocity distribution upstream of the suction slot and by selecting suction peak position and solidity. A three-dimensional (3D) highly loaded aspirated cascade was designed based on a two-dimensional (2D) cascade. Both the trailing edge separation and corner separation of the 3D highly loaded aspirated cascade were eliminated successfully with coupled suction surface and endwall suction.

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Svetukhin, Viacheslav, and Mikhail Tikhonchev. "Effective Atomic Displacements in Fe-9at.%Cr Alloy." Defect and Diffusion Forum 375 (May 2017): 139–49. http://dx.doi.org/10.4028/www.scientific.net/ddf.375.139.

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A computer simulation of atomic displacement cascades in Fe-9at.%Cr binary alloy has been performed by molecular dynamics method for temperature of 300 K and cascade energies from 100 eV to 20 keV. The average number of Frenkel pairs produced in cascade has been calculated. The data on point defect clusterization have been obtained. Obtained evaluations of effective fraction of surviving defects are well approximated by the sum of power and linear functions of cascade energy. Increased chromium fraction in the self-interstitial (SIA) configurations has been observed and has been explained by combination of two factors: positive binding energy of Cr atom with SIAs and mobility of SIA configuration. The diffusion coefficient of single SIA configuration in the matrix of pure bcc Fe has been evaluated for the temperature range of 300 – 1000 K. We have prepared 100 group neutron cross-sections of effective displacement generation in Fe-9at.%Cr binary alloy. It has been shown that effective dpa generation rate can be 2-3 times lower than corresponding rates of conventional dpa generation rate.

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Alurralde, M., A. Caro, and M. Victoria. "Influence of the irradiation temperature on the intracascade ion mixing." Journal of Materials Research 8, no. 3 (March 1993): 449–54. http://dx.doi.org/10.1557/jmr.1993.0449.

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We present a description of the thermal behavior of cascades in Cu and Ag over a large energy range and irradiation temperatures. For this purpose the binary collision approximation, which gives the profile of the energy deposition, is coupled to a simplified version of the heat equation. In the present calculations, the original liquid drop model [M. Alurralde, A. Caro, and M. Victoria, J. Nucl. Mater. 183, 33 (1991)] has been extended to the case where the lattice is at finite temperatures. The resulting evolution of the liquid cascade is analyzed for PKA energies up to 1 MeV, and the results are compared to experimental observations of mixing rates. We obtain a temperature dependence that adds to the traditional Radiation Enhanced Diffusion, RED, in very good qualitative agreement with experiments on materials showing thermal spikes.

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Liang, Hai. "Decreasing social contagion effects in diffusion cascades: Modeling message spreading on social media." Telematics and Informatics 62 (September 2021): 101623. http://dx.doi.org/10.1016/j.tele.2021.101623.

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Golder, Peter N., and Gerard J. Tellis. "Growing, Growing, Gone: Cascades, Diffusion, and Turning Points in the Product Life Cycle." Marketing Science 23, no. 2 (May 2004): 207–18. http://dx.doi.org/10.1287/mksc.1040.0057.

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Yong, You, Pingkai Ouyang, Jianzhong Wu, and Zheng Liu. "A Diffusion‐Reaction Model for One‐Pot Synthesis of Chemicals with Enzyme Cascades." ChemCatChem 12, no. 2 (December 2, 2019): 528–35. http://dx.doi.org/10.1002/cctc.201901161.

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Poiitis, Marinos, Athena Vakali, and Nicolas Kourtellis. "On the Aggression Diffusion Modeling and Minimization in Twitter." ACM Transactions on the Web 16, no. 1 (February 28, 2022): 1–24. http://dx.doi.org/10.1145/3486218.

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Aggression in online social networks has been studied mostly from the perspective of machine learning, which detects such behavior in a static context. However, the way aggression diffuses in the network has received little attention as it embeds modeling challenges. In fact, modeling how aggression propagates from one user to another is an important research topic, since it can enable effective aggression monitoring, especially in media platforms, which up to now apply simplistic user blocking techniques. In this article, we address aggression propagation modeling and minimization in Twitter, since it is a popular microblogging platform at which aggression had several onsets. We propose various methods building on two well-known diffusion models, Independent Cascade ( IC ) and Linear Threshold ( LT ), to study the aggression evolution in the social network. We experimentally investigate how well each method can model aggression propagation using real Twitter data, while varying parameters, such as seed users selection, graph edge weighting, users’ activation timing, and so on. It is found that the best performing strategies are the ones to select seed users with a degree-based approach, weigh user edges based on their social circles’ overlaps, and activate users according to their aggression levels. We further employ the best performing models to predict which ordinary real users could become aggressive (and vice versa) in the future, and achieve up to AUC = 0.89 in this prediction task. Finally, we investigate aggression minimization by launching competitive cascades to “inform” and “heal” aggressors. We show that IC and LT models can be used in aggression minimization, providing less intrusive alternatives to the blocking techniques currently employed by Twitter.

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Agouzoul, M., and R. Camarero. "Numerical Computation of Two-Dimensional Turbulent Flow In a Cascade." Transactions of the Canadian Society for Mechanical Engineering 12, no. 2 (June 1988): 105–14. http://dx.doi.org/10.1139/tcsme-1988-0015.

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A numerical method for modelling and predicting steady two-dimensional turbulent flows for turbomachinery elements such as cascades is presented. The average motion equations are formulated in vorticity-stream function variables. The Reynolds stresses are modelled with the eddy viscosity concept, based on the Boussinesq hypothesis. The eddy viscosity is calculated with the k-ϵ model. The pressure is recovered by a Poisson equation. In order to solve flows in complex geometries, the equations are written in a generalised curvalinear coordinate system. These are then discretised using a centered finite differences for diffusion terms while for the convective terms third-order-accurate upwinding is used, to minimize the artificial diffusion.

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Sato, T., S. Aoki, and T. Nagayama. "Extensive Verification of the Denton New Scheme From the User’s Point of View: Part II—Comparison of Calculated and Experimental Results." Journal of Turbomachinery 108, no. 2 (October 1, 1986): 170–77. http://dx.doi.org/10.1115/1.3262032.

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A blade-to-blade flow program incorporated in the computer-aided turbine design system is required to have short run times, robustness, and no limitations. The Denton time-marching method published in 1982 is attractive as it is fast and can handle mixed subsonic-supersonic flows. Calibration of code control variables is discussed in part I. In this paper, the scheme is extensively verified by comparing calculated surface Mach number distributions with experimental data obtained from two-dimensional cascade tests for 23 cascades. For the nozzles, excellent agreement is obtained if the flows are fully subsonic, or transonic with weak shock–boundary layer interaction. For the blades, very good agreement is also obtained if the blades have moderate blade reaction and viscous effects are small. Satisfactory results are obtained for suction surface diffusion, even at off-design inlet conditions, if absolute values of incidence angle are less than 10 deg.

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Demidov, Dmitry N., Alexander B. Sivak, and Polina A. Sivak. "New Method for Calculation of Radiation Defect Dipole Tensor and Its Application to Di-Interstitials in Copper." Symmetry 13, no. 7 (June 27, 2021): 1154. http://dx.doi.org/10.3390/sym13071154.

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The effect of external and internal elastic strain fields on the anisotropic diffusion of radiation defects (RDs) can be taken into account if one knows the dipole tensor of saddle-point configurations of the diffusing RDs. It is usually calculated by molecular statics, since the insufficient accuracy of the available experimental techniques makes determining it experimentally difficult. However, for an RD with multiple crystallographically non-equivalent metastable and saddle-point configurations (as in the case of di-interstitials), the problem becomes practically unsolvable due to its complexity. In this paper, we used a different approach to solving this problem. The molecular dynamics (MD) method was used to calculate the strain dependences of the RD diffusion tensor for various types of strain states. These dependences were used to determine the dipole tensor of the effective RD saddle-point configuration, which takes into account the contributions of all real saddle-point configurations. The proposed approach was used for studying the diffusion characteristics of RDs, such as di-interstitials in FCC copper (used in plasma-facing components of fusion reactors under development). The effect of the external elastic field on the MD-calculated normalized diffusion tensor (ratio of the diffusion tensor to a third of its trace) of di-interstitials was fully consistent with analytical predictions based on the kinetic theory, the parameters of which were the components of the dipole tensors, including the range of non-linear dependence of the diffusion tensor on strains. The results obtained allowed for one to simulate the anisotropic diffusion of di-interstitials in external and internal elastic fields, and to take into account the contribution of di-interstitials to the radiation deformation of crystals. This contribution can be significant, as MD data on the primary radiation damage in copper shows that ~20% of self-interstitial atoms produced by cascades of atomic collisions are combined into di-interstitials.

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Cao, Qi, Huawei Shen, Jinhua Gao, and Xueqi Cheng. "Learning diffusion model-free and efficient influence function for influence maximization from information cascades." Knowledge and Information Systems 63, no. 5 (March 19, 2021): 1173–96. http://dx.doi.org/10.1007/s10115-021-01556-6.

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Filipov, Yaroslav, Andrey Zakharchenko, Sergiy Minko, and Evgeny Katz. "Magneto-Controlled Biocatalytic Cascades with Logically Processed Input Signals - Substrate Channeling versus Free Diffusion." ChemPhysChem 19, no. 22 (October 19, 2018): 3035–43. http://dx.doi.org/10.1002/cphc.201800851.

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Journal articles on the topic 'Diffusion cascades'

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