Bursts of communication increase opinion diversity in the temporal Deffuant model.

Human interactions create social networks forming the backbone of societies. Individuals adjust their opinions by exchanging information through social interactions. Two recurrent questions are whether social structures promote opinion polarisation or consensus and whether polarisation can be avoided, particularly on social media.

Evolution of Public Opinion on COVID-19 Vaccination in Japan: Large-Scale Twitter Data Analysis.

Background: Vaccines are promising tools to control the spread of COVID-19. An effective vaccination campaign requires government policies and community engagement, sharing experiences for social support, and voicing concerns about vaccine safety and efficiency. The increasing use of online social platforms allows us to trace large-scale communication and infer public opinion in real time.

Maximum entropy networks for large scale social network node analysis.

Recently proposed computational techniques allow the application of various maximum entropy network models at a larger scale. We focus on disinformation campaigns and apply different maximum entropy network models on the collection of datasets from the Twitter information operations report. For each dataset, we obtain additional Twitter data required to build an interaction network.

LargeNetVis: Visual Exploration of Large Temporal Networks Based on Community Taxonomies.

Temporal (or time-evolving) networks are commonly used to model complex systems and the evolution of their components throughout time. Although these networks can be analyzed by different means, visual analytics stands out as an effective way for a pre-analysis before doing quantitative/statistical analyses to identify patterns, anomalies, and other behaviors in the data, thus leading to new insights and better decision-making. However, the large number of nodes, edges, and/or timestamps in many real-world networks may lead to polluted layouts that make the analysis inefficient or even infeasible.

The global migration network of sex-workers.

Differences in the social and economic environment across countries encourage humans to migrate in search of better living conditions, including job opportunities, higher salaries, security and welfare. Quantifying global migration is, however, challenging because of poor recording, privacy issues and residence status. This is particularly critical for some classes of migrants involved in stigmatised, unregulated or illegal activities.

The scaling of social interactions across animal species.

Social animals self-organise to create groups to increase protection against predators and productivity. One-to-one interactions are the building blocks of these emergent social structures and may correspond to friendship, grooming, communication, among other social relations. These structures should be robust to failures and provide efficient communication to compensate the costs of forming and maintaining the social contacts but the specific purpose of each social interaction regulates the evolution of the respective social networks.

A qualitative assessment in acceptability and barriers to use pre-exposure prophylaxis (PrEP) among men who have sex with men: implications for service delivery in Vietnam.

Background: HIV Pre-exposure prophylaxis (PrEP) is being considered for implementation among MSM nationwide in Vietnam. However, there may be concerns about potential obstacles for PrEP adherence among Vietnamese MSM. This study aims to assess the acceptability to use PrEP, potential barriers and facilitators, and the preferences for PrEP service accessibility and delivery among Vietnamese MSM.

Applications and Recruitment Performance of Web-Based Respondent-Driven Sampling: Scoping Review.

Background: Web-based respondent-driven sampling is a novel sampling method for the recruitment of participants for generating population estimates, studying social network characteristics, and delivering health interventions. However, the application, barriers and facilitators, and recruitment performance of web-based respondent-driven sampling have not yet been systematically investigated.

Objective: Our objectives were to provide an overview of published research using web-based respondent-driven sampling and to investigate factors related to the recruitment performance of web-based respondent-driven sampling.

On the connection between real-world circumstances and online player behaviour: The case of EVE Online.

Games involving virtual worlds are popular in several segments of the population and societies. The online environment facilitates that players from different countries interact in a common virtual world. Virtual worlds involving social and economic interactions are particularly useful to test social and economic theories.

An exploratory assessment of the preference for eHealth interventions to prevent HIV and sexually transmitted infections among men who have sex with men in Hanoi, Vietnam.

Background: Electronic health (eHealth) interventions are promising in HIV and sexually transmitted infections (STIs) prevention among men who have sex with men (MSM), given a high rate of the Internet use in this population. This study determined the preferences for eHealth interventions to prevent HIV and STIs among MSM in Hanoi, Vietnam to guide the development of future eHealth interventions.

Methods: Five focus group discussions (FGD) were conducted with 35 MSM recruited by purposive sampling in January 2018 in Hanoi, Vietnam.

Dynamic contact networks of patients and MRSA spread in hospitals.

Methicillin-resistant Staphylococcus aureus (MRSA) is a difficult-to-treat infection. Increasing efforts have been taken to mitigate the epidemics and to avoid potential outbreaks in low endemic settings. Understanding the population dynamics of MRSA is essential to identify the causal mechanisms driving the epidemics and to generalise conclusions to different contexts.

Clustering of chronic hepatitis B screening intentions in social networks of Moroccan immigrants in the Netherlands.

Background: Early detection, identification, and treatment of chronic hepatitis B through screening is vital for those at increased risk, e.g. born in hepatitis B endemic countries.

A Systematic Review of eHealth Interventions Addressing HIV/STI Prevention Among Men Who Have Sex With Men.

A systematic review was conducted to summarize and appraise the eHealth interventions addressing HIV/STI prevention among men who have sex with men (MSM), and characterize features of successful eHealth interventions. Fifty-five articles (17 pilots and 38 full efficacy trials) were included with the predominance of web-based interventions in the United States-based settings. Intervention modalities include web-based, short message service (SMS)/text messges/email reminder, online video-based, computer-assisted, multimedia-based, social network, live chat and chat room, virtual simulation intervention, and smartphone applications.

Assessing Student's Achievement Gaps between Ethnic Groups in Brazil.

Achievement gaps refer to the difference in the performance on assessments of students belonging to different social groups. Achievement gaps between ethnic groups have been observed in countries with heterogeneous populations. In this paper, achievement gaps between ethnic populations in Brazil were analyzed by studying the performance of a large cohort of senior high-school students in a standardized national exam.

Modelling opinion dynamics in the age of algorithmic personalisation.

Modern technology has drastically changed the way we interact and consume information. For example, online social platforms allow for seamless communication exchanges at an unprecedented scale. However, we are still bounded by cognitive and temporal constraints.

Sampling of temporal networks: Methods and biases.

Temporal networks have been increasingly used to model a diversity of systems that evolve in time; for example, human contact structures over which dynamic processes such as epidemics take place. A fundamental aspect of real-life networks is that they are sampled within temporal and spatial frames. Furthermore, one might wish to subsample networks to reduce their size for better visualization or to perform computationally intensive simulations.

Correlations and forecast of death tolls in the Syrian conflict.

The Syrian armed conflict has been ongoing since 2011 and has already caused thousands of deaths. The analysis of death tolls helps to understand the dynamics of the conflict and to better allocate resources and aid to the affected areas. In this article, we use information on the daily number of deaths to study temporal and spatial correlations in the data, and exploit this information to forecast events of deaths.

Individual-based approach to epidemic processes on arbitrary dynamic contact networks.

The dynamics of contact networks and epidemics of infectious diseases often occur on comparable time scales. Ignoring one of these time scales may provide an incomplete understanding of the population dynamics of the infection process. We develop an individual-based approximation for the susceptible-infected-recovered epidemic model applicable to arbitrary dynamic networks.

Temporal and structural heterogeneities emerging in adaptive temporal networks.

We introduce a model of adaptive temporal networks whose evolution is regulated by an interplay between node activity and dynamic exchange of information through links. We study the model by using a master equation approach. Starting from a homogeneous initial configuration, we show that temporal and structural heterogeneities, characteristic of real-world networks, spontaneously emerge.

The Non-linear Health Consequences of Living in Larger Cities.

Urbanization promotes economy, mobility, access, and availability of resources, but on the other hand, generates higher levels of pollution, violence, crime, and mental distress. The health consequences of the agglomeration of people living close together are not fully understood. Particularly, it remains unclear how variations in the population size across cities impact the health of the population.

Diffusion on networked systems is a question of time or structure.

Network science investigates the architecture of complex systems to understand their functional and dynamical properties. Structural patterns such as communities shape diffusive processes on networks. However, these results hold under the strong assumption that networks are static entities where temporal aspects can be neglected.

Flow motifs reveal limitations of the static framework to represent human interactions.

Networks are commonly used to define underlying interaction structures where infections, information, or other quantities may spread. Although the standard approach has been to aggregate all links into a static structure, some studies have shown that the time order in which the links are established may alter the dynamics of spreading. In this paper, we study the impact of the time ordering in the limits of flow on various empirical temporal networks.

Bursts of vertex activation and epidemics in evolving networks.

The dynamic nature of contact patterns creates diverse temporal structures. In particular, empirical studies have shown that contact patterns follow heterogeneous inter-event time intervals, meaning that periods of high activity are followed by long periods of inactivity. To investigate the impact of these heterogeneities in the spread of infection from a theoretical perspective, we propose a stochastic model to generate temporal networks where vertices make instantaneous contacts following heterogeneous inter-event intervals, and may leave and enter the system.

Exploiting temporal network structures of human interaction to effectively immunize populations.

Decreasing the number of people who must be vaccinated to immunize a community against an infectious disease could both save resources and decrease outbreak sizes. A key to reaching such a lower threshold of immunization is to find and vaccinate people who, through their behavior, are more likely than average to become infected and to spread the disease further. Fortunately, the very behavior that makes these people important to vaccinate can help us to localize them.