Online networks and subjective well-being

We argue that the use of online networks may threaten subjective well-being in several ways, due to the inherent attributes of Internet-mediated interaction and through its effects on social trust and sociability. We test our hypotheses on a representative sample of the Italian population. We find a significantly negative correlation between online networking and well-being. This result is partially confirmed after accounting for endogeneity. We explore the direct and indirect effects of the use of social networking sites (SNS) on well-being in a SEM analysis. We find that online networking plays a positive role in subjective well-being through its impact on physical interactions, whereas SNS use is associated with lower social trust. The overall effect of networking on individual welfare is significantly negative.Comment: 40 page

Causal Inference in Disease Spread across a Heterogeneous Social System

Diffusion processes are governed by external triggers and internal dynamics in complex systems. Timely and cost-effective control of infectious disease spread critically relies on uncovering the underlying diffusion mechanisms, which is challenging due to invisible causality between events and their time-evolving intensity. We infer causal relationships between infections and quantify the reflexivity of a meta-population, the level of feedback on event occurrences by its internal dynamics (likelihood of a regional outbreak triggered by previous cases). These are enabled by our new proposed model, the Latent Influence Point Process (LIPP) which models disease spread by incorporating macro-level internal dynamics of meta-populations based on human mobility. We analyse 15-year dengue cases in Queensland, Australia. From our causal inference, outbreaks are more likely driven by statewide global diffusion over time, leading to complex behavior of disease spread. In terms of reflexivity, precursory growth and symmetric decline in populous regions is attributed to slow but persistent feedback on preceding outbreaks via inter-group dynamics, while abrupt growth but sharp decline in peripheral areas is led by rapid but inconstant feedback via intra-group dynamics. Our proposed model reveals probabilistic causal relationships between discrete events based on intra- and inter-group dynamics and also covers direct and indirect diffusion processes (contact-based and vector-borne disease transmissions).Comment: arXiv admin note: substantial text overlap with arXiv:1711.0635