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Influencing others through social networks is fundamental to all human societies. Whether this happens through the diffusion of rumors, opinions, or viruses, identifying the diffusion source (i.e., the person that initiated it) is a problem that has attracted much research interest. Nevertheless, existing literature has ignored the possibility that the source might strategically modify the network structure (by rewiring links or introducing fake nodes) to escape detection. Here, without restricting our analysis to any particular diffusion scenario, we close this gap by evaluating two mechanisms that hide the source-one stemming from the source's actions, the other from the network structure itself. This reveals that sources can easily escape detection, and that removing links is far more effective than introducing fake nodes. Thus, efforts should focus on exposing concealed ties rather than planted entities; such exposure would drastically improve our chances of detecting the diffusion source.

Culture has played a pivotal role in human evolution. Yet, the ability of social scientists to study culture is limited by the currently available measurement instruments. Scholars of culture must regularly choose between scalable but sparse survey-based methods or restricted but rich ethnographic methods. Here, we demonstrate that massive online social networks can advance the study of human culture by providing quantitative, scalable and high-resolution measurement of behaviourally revealed cultural values and preferences. We employ data across nearly 60 000 topic dimensions drawn from two billion Facebook users across 225 countries and territories. We first validate that cultural distances calculated from this measurement instrument correspond to traditional survey-based and objective measures of cross-national cultural differences. We then demonstrate that this expanded measure enables rich insight into the cultural landscape globally at previously impossible resolution. We analyse the importance of national borders in shaping culture and compare subnational divisiveness with gender divisiveness across countries. Our measure enables detailed investigation into the geopolitical stability of countries, social cleavages within small- and large-scale human groups, the integration of migrant populations and the disaffection of certain population groups from the political process, among myriad other potential future applications.

As the COVID-19 pandemic has demonstrated, identifying the origin of a pandemic remains a challenging task. The search for patient zero may benefit from the widely-used and well-established toolkit of contact tracing methods, although this possibility has not been explored to date. We fill this gap by investigating the prospect of performing the source detection task as part of the contact tracing process, i.e., the possibility of tuning the parameters of the process in order to pinpoint the origin of the infection. To this end, we perform simulations on temporal networks using a recent diffusion model that recreates the dynamics of the COVID-19 pandemic. We find that increasing the budget for contact tracing beyond a certain threshold can significantly improve the identification of infected individuals but has diminishing returns in terms of source detection. Moreover, disease variants of higher infectivity make it easier to find the source but harder to identify infected individuals. Finally, we unravel a seemingly-intrinsic trade-off between the use of contact tracing to either identify infected nodes or detect the source of infection. This trade-off suggests that focusing on the identification of patient zero may come at the expense of identifying infected individuals.

The world has recently witnessed several disasters, wherein the human cost of the catastrophe depended strongly on the delivery time of critical rescue information, mostly through strangers, on the location and status of individuals. Unfortunately, these are often situations wherein technology ceases to function. Pen-and-paper solutions then become the only viable option for information transfer. Both the propagation of information in networks and social search through traditional digital devices such as mobile phones and e-mails is welldocumented in the literature. However, existing models usually fail to take into account the cost of the physical propagation of information. We report on the empirical results of a pen-andpaper system involving time-critical approximate social search. In particular, participants'goal is to locate and assess the status of other participants without further knowledge regarding their identity. We show that when there is a cost associated with information propagation, the network efficiency is mainly driven by the presence of strongly motivated individuals who actively seek to acquire and propagate information. © 2011 IEEE.

The world has recently witnessed several disasters, wherein the human cost of the catastrophe depended strongly on the delivery time of critical rescue information, mostly through strangers, on the location and status of individuals. Unfortunately, these are often situations wherein technology ceases to function. Pen-and-paper solutions then become the only viable option for information transfer. Both the propagation of information in networks and social search through traditional digital devices such as mobile phones and e-mails is welldocumented in the literature. However, existing models usually fail to take into account the cost of the physical propagation of information. We report on the empirical results of a pen-andpaper system involving time-critical approximate social search. In particular, participants'goal is to locate and assess the status of other participants without further knowledge regarding their identity. We show that when there is a cost associated with information propagation, the network efficiency is mainly driven by the presence of strongly motivated individuals who actively seek to acquire and propagate information. © 2011 IEEE.

© 2017 International World Wide Web Conference Committee (IW3C2) Modeling and predicting the popularity of online content is a significant problem for the practice of information dissemination, advertising, and consumption. Recent work analyzing massive datasets advances our understanding of popularity, but one major gap remains: To precisely quantify the relationship between the popularity of an online item and the external promotions it receives. This work supplies the missing link between exogenous inputs from public social media platforms, such as Twitter, and endogenous responses within the content platform, such as YouTube. We develop a novel mathematical model, the Hawkes intensity process, which can explain the complex popularity history of each video according to its type of content, network of diffusion, and sensitivity to promotion. Our model supplies a prototypical description of videos, called an endo-exo map. This map explains popularity as the result of an extrinsic factor – the amount of promotions from the outside world that the video receives, acting upon two intrinsic factors – sensitivity to promotion, and inherent virality. We use this model to forecast future popularity given promotions on a large 5-months feed of the most-tweeted videos, and found it to lower the average error by 28.6% from approaches based on popularity history. Finally, we can identify videos that have a high potential to become viral, as well as those for which promotions will have hardly any effect.