From Chatter to Action: How Social Networks Inform and Motivate in Rural Uganda

From public health to political campaigns, numerous attempts to encourage behavior begin with the spread of information. Of course, seeding new information does not guarantee action, especially when it is difficult for receivers to verify this information. We use a novel design that introduced valuable, actionable information in rural Uganda and reveals the intermediate process that led many in the village to hear the information but only some to act on it. We find that the seeded information spread easily through word of mouth via a simple contagion process. However, acting on the information spread less easily; this process relied instead on endogenously created social information that served to vet, verify, and pass judgment. Our results highlight an important wedge between information that a policy intervention can best control and the behavior that ultimately results.

The Relationship Between Olfactory Function and Emotional Contagion

Introduction Research has provided evidence for the transfer of single emotions including anger, anxiety and happiness through olfactory chemosignals, yet no work has examined the role of odour function in the aggregation of more complex emotional states or in the emotional contagion process. The aim of the present study was to ascertain whether an individual’s tendency to experience emotional aggregation was affected by objective measures of their olfactory function and subjective self-assessments of the importance of their own olfactory system. Methods In this study (N = 70), participant pairs were first assessed individually for olfactory threshold and odour identification, then completed the Importance of Olfaction Questionnaire. Each pair subsequently took part in two collaborative tasks. Individual emotion measures were taken before, during and after the completion of the two tasks. Results Multilevel structural equation modelling revealed that individuals’ within-dyad positive emotional agreement scores were associated with both their ‘importance of olfaction’ scores and their olfactory function. A significant association was also found between olfactory performance and the Importance of Olfaction scores. Conclusions These results provide evidence that the subjective importance an individual assigns to their sense of smell can predict their susceptibility to experience emotional aggregation during active, collaborative tasks. Implications The findings suggest that individuals’ tendency and capability to detect and respond to emotional chemosignals, a process required for olfactory-facilitated emotional contagion, may be affected by individual differences in olfactory function and subjective attitudes toward olfaction.

Financial Contagion Patterns in Individual Economic Sectors. The Day-of-the-Week Effect from the Polish, Russian and Romanian Markets

This paper studies the presence of the day-of-the-week (DOW) effect in the financial contagion process observed on individual economic sectors from the Post-Communist East European markets. The only markets that provide national-specific sector indices determined throughout the 2008 financial crisis are Poland, Romania and Russia. The novel methodology combines two existing perspectives from financial literature, by employing a GJR-GARCH framework on a dummy regression model that accounts for both the crisis period and the weekdays. All indices show the presence of the DOW effect during the crisis and/or non-crisis periods, thus signaling their low level of market efficiency. However, the contagion process affects only eight of these indices: the banking, IT and oil and gas sectors from Poland, the chemical, telecommunication and transport sectors from Russia and energy sectors from Russia and Romania. All of them show signs of the DOW effect in contagion: five exhibit higher spillovers on crisis Mondays, while the other three show other weekday patterns. The findings suggest that the DOW effect is not specific to certain countries or certain economic sectors.

Domestic and Foreign Transmission of the Global Financial Crisis in the Real Economy. The Polish Situation

This paper studies the contagion process of the 2008 Global Financial Crisis through several important Polish economic sectors: chemical, construction, food, IT, media, oil & gas and telecommunication. The results show a signiÖcant di§erence between the response of these sectors to the crisis. Chemical, construction, media and oil and gas were a§ected, in di§erent degrees, by a domestic Önancial contagion. The food industry was ináuenced in a negligible degree by contagion, while the IT and telecommunication sectors showed a decrease of their co-movements with the Önancial sector, both foreign and domestic.

A systematic framework of modelling epidemics on temporal networks

We present a modelling framework for the spreading of epidemics on temporal networks from which both the individual-based and pair-based models can be recovered. The proposed temporal pair-based model that is systematically derived from this framework offers an improvement over existing pair-based models by moving away from edge-centric descriptions while keeping the description concise and relatively simple. For the contagion process, we consider the susceptible–infected–recovered (SIR) model, which is realized on a network with time-varying edges. We show that the shift in perspective from individual-based to pair-based quantities enables exact modelling of Markovian epidemic processes on temporal tree networks. On arbitrary networks, the proposed pair-based model provides a substantial increase in accuracy at a low computational and conceptual cost compared to the individual-based model. From the pair-based model, we analytically find the condition necessary for an epidemic to occur, otherwise known as the epidemic threshold. Due to the fact that the SIR model has only one stable fixed point, which is the global non-infected state, we identify an epidemic by looking at the initial stability of the model.

Continuous learning and inference of individual probability of SARS-CoV-2 infection based on interaction data

This study presents a new approach to determine the likelihood of asymptomatic carriers of the SARS-CoV-2 virus by using interaction-based continuous learning and inference of individual probability (CLIIP) for contagious ranking. This approach is developed based on an individual directed graph (IDG), using multi-layer bidirectional path tracking and inference searching. The IDG is determined by the appearance timeline and spatial data that can adapt over time. Additionally, the approach takes into consideration the incubation period and several features that can represent real-world circumstances, such as the number of asymptomatic carriers present. After each update of confirmed cases, the model collects the interaction features and infers the individual person’s probability of getting infected using the status of the surrounding people. The CLIIP approach is validated using the individualized bidirectional SEIR model to simulate the contagion process. Compared to traditional contact tracing methods, our approach significantly reduces the screening and quarantine required to search for the potential asymptomatic virus carriers by as much as 94%.

FINANCIAL CONTAGION IN A STOCHASTIC BLOCK MODEL

One of the most characteristic features of the global financial network is its inherently complex and intertwined structure. From the perspective of systemic risk it is important to understand the influence of this network structure on default contagion. Using sparse random graphs to model the financial network, asymptotic methods turned out to be powerful for the purpose of analytically describing the contagion process and making statements about resilience. So far, however, such methods have been limited to so-called rank-one models in which, informally speaking, the only parameter for the skeleton of the network is the degree sequence and the contagion process can be described by a one-dimensional fixed-point equation. Such networks fail to account for the possibility of a pronounced block structure such as core/periphery or a network composed of different connected blocks for different countries. We present a much more general model here, where we distinguish vertices (institutions) of different types and let edge probabilities and exposures depend on the types of both, the receiving and the sending vertex, plus additional parameters. Our main result allows one to compute explicitly the systemic damage caused by some initial local shock event, and we derive a complete characterization of resilient and nonresilient financial systems. This is the first instance that default contagion is rigorously studied in a model outside the class of rank-one models and several technical challenges arise. In contrast to previous work, in which networks could be classified as resilient or nonresilient independently of the distribution of the shock, information about the shock becomes important in our model and a more refined resilience condition arises. Among other applications of our theory we derive resilience conditions for the global network based on subnetwork conditions only.

Crisis contagion in the world trade network

We present a model of worldwide crisis contagion based on the Google matrix analysis of the world trade network obtained from the UN Comtrade database. The fraction of bankrupted countries exhibits an on-off phase transition governed by a bankruptcy threshold κ related to the trade balance of the countries. For κ>κc, the contagion is circumscribed to less than 10% of the countries, whereas, for κ<κc, the crisis is global with about 90% of the countries going to bankruptcy. We measure the total cost of the crisis during the contagion process. In addition to providing contagion scenarios, our model allows to probe the structural trading dependencies between countries. For different networks extracted from the world trade exchanges of the last two decades, the global crisis comes from the Western world. In particular, the source of the global crisis is systematically the Old Continent and The Americas (mainly US and Mexico). Besides the economy of Australia, those of Asian countries, such as China, India, Indonesia, Malaysia and Thailand, are the last to fall during the contagion. Also, the four BRIC are among the most robust countries to the world trade crisis.

A review on Poisson, Cox, Hawkes, shot-noise Poisson and dynamic contagion process and their compound processes

The Poisson process is an essential building block to move up to complicated counting processes, such as the Cox (“doubly stochastic Poisson”) process, the Hawkes (“self-exciting”) process, exponentially decaying shot-noise Poisson (simply “shot-noise Poisson”) process and the dynamic contagion process. The Cox process provides flexibility by letting the intensity not only depending on time but also allowing it to be a stochastic process. The Hawkes process has self-exciting property and clustering effects. Shot-noise Poisson process is an extension of the Poisson process, where it is capable of displaying the frequency, magnitude and time period needed to determine the effect of points. The dynamic contagion process is a point process, where its intensity generalises the Hawkes process and Cox process with exponentially decaying shot-noise intensity. To facilitate the usage of these processes in practice, we revisit the distributional properties of the Poisson, Cox, Hawkes, shot-noise Poisson and dynamic contagion process and their compound processes. We provide simulation algorithms for these processes, which would be useful to statistical analysis, further business applications and research. As an application of the compound processes, numerical comparisons of value-at-risk and tail conditional expectation are made.