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This thesis can be categorized under the Influencer Marketing industry with respect to social media initiatives. Influencer marketing is a modern tactic used by brands to enhance their visibility to their target audience by using the…

Network-based interventions against epidemic spread are most powerful when the full network structure is known. However, in practice, resource constraints require decisions to be made based on partial network information. We investigated…

Evaluating the impact of policy interventions on respondents who are embedded in a social network is often challenging due to the presence of network interference within the treatment groups, as well as between treatment and non-treatment…

Amidst COVID-19 misinformation spreading, social media platforms like Facebook and Twitter rolled out design interventions, including banners linking to authoritative resources and more specific "false information" labels. In late March…

Augmenting classical epidemiological models with information from the social sciences helps unveil the interplay between contagion dynamics and social responses. However, multidisciplinary integration of social analysis and epidemiological…

Social media platforms have transformed the dynamics of collective opinion formation, enabling rapid, large-scale interactions while simultaneously exposing online discourse to polarization and manipulation. Traditional models of opinion…

Predicting mental health from smartphone and social media data on a longitudinal basis has recently attracted great interest, with very promising results being reported across many studies. Such approaches have the potential to…

An ability to infer the political leaning of social media users can help in gathering opinion polls thereby leading to a better understanding of public opinion. While there has been a body of research attempting to infer the political…

Process mining is a discipline sitting between data mining and process science, whose goal is to provide theoretical methods and software tools to analyse process execution data, known as event logs. Although process mining was originally…

For many people, social media is an important way to consume news on important topics like health. Unfortunately, some influential health news is misinformation because it is based on retracted scientific work. Ours is the first work to…

The pervasive use of social media has grown to over two billion users to date, and is commonly utilized as a means to share information and shape world events. Evidence suggests that passive social media usage (i.e., viewing without taking…

The prevalence of coordinated information campaigns in social media platforms has significant negative consequences across various domains, including social, political, and economic processes. This paper proposes a multifaceted framework…

Online data has the potential to transform how researchers and companies produce election forecasts. Social media surveys, online panels and even comments scraped from the internet can offer valuable insights into political preferences.…

In recent years, we have witnessed the proliferation of large amounts of online content generated directly by users with virtually no form of external control, leading to the possible spread of misinformation. The search for effective…

The decision of whether or not to vaccinate is a complex one. It involves the contribution both to a social good -- herd immunity -- and to one's own well being. It is informed by social influence, personal experience, education, and mass…

In the past decade, tracking health trends using social media data has shown great promise, due to a powerful combination of massive adoption of social media around the world, and increasingly potent hardware and software that enables us to…

Diffusion processes in networks are increasingly used to model the spread of information and social influence. In several applications in computational sustainability such as the spread of wildlife, infectious diseases and traffic mobility…

Social media have become a rich source of data, particularly in health research. Yet, the use of such data raises significant ethical questions about the need for the informed consent of those being studied. Consent mechanisms, if even…

This paper investigates the spread of infectious diseases within a networked community by integrating epidemic transmission and public opinion dynamics. We propose a novel discrete-time networked SIS (Susceptible-Infectious-Susceptible)…

Epidemic models play a key role in understanding and responding to the emerging COVID-19 pandemic. Widely used compartmental models are static and are of limited use to evaluate intervention strategies with the emerging pandemic. Applying…