Social data in digital form—including user-generated content, expressed or implicit relations
between people, and behavioral traces—are at the core of popular applications and …

The use of social network theory and analysis methods as applied to public health has
expanded greatly in the past decade, yielding a significant academic literature that spans …

" Human-centered machine learning"(HCML) combines human insights and domain
expertise with data-driven predictions to answer societal questions. This area's inherent …

A potentially powerful method of social-scientific data collection and investigation has been
created by an unexpected institution: the law. Article 15 of the EU's 2018 General Data …

Social media (SM) offer huge potential for public health research, serving as a vehicle for
surveillance, delivery of health interventions, recruitment to trials, collection of data, and …

This accessible, alphabetical guide provides concise insights into a variety of digital
research methods, incorporating introductory knowledge with practical application and …

Social media platforms capture and trade consumer data for analysis, user profiling and for
sale to interested parties and is used extensively in marketing. To collect, store, process and …

The ubiquity of digital devices and the increasing intensity of users' interactions with them
create vast amounts of digital trace data. Companies use these data to optimize their …

Applied machine learning (ML) has not yet coalesced on standard practices for research
ethics. For ML that predicts mental illness using social media data, ambiguous ethical …

Dynamic consent (DC) is an approach to consent that enables people, through an
interactive digital interface, to make granular decisions about their ongoing participation …