Graph representation learning aims to effectively encode high-dimensional sparse graph-
structured data into low-dimensional dense vectors, which is a fundamental task that has …

Scientists are enthusiastically imagining ways in which artificial intelligence (AI) tools might
improve research. Why are AI tools so attractive and what are the risks of implementing them …

Machine-learning (ML) methods have gained prominence in the quantitative sciences.
However, there are many known methodological pitfalls, including data leakage, in ML …

In a time of societal acrimony, psychological scientists have turned to a possible antidote—
intellectual humility. Interest in intellectual humility comes from diverse research areas …

The movements of individuals within and among cities influence critical aspects of our
society, such as well-being, the spreading of epidemics, and the quality of the environment …

The advent of large-scale datasets that trace the workings of science has encouraged
researchers from many different disciplinary backgrounds to turn scientific methods into …

The dominant paradigm of experiments in the social and behavioral sciences views an
experiment as a test of a theory, where the theory is assumed to generalize beyond the …

Due to the methodological challenges inherent in studying social media use (SMU), as well
as the methodological choices that have shaped research into the effects of SMU on well …

Traditionally, scientists have placed more emphasis on communicating inferential
uncertainty (ie, the precision of statistical estimates) compared to outcome variability (ie, the …

Dengue is expanding globally, but how dengue emergence is shaped locally by interactions
between climatic and socio-environmental factors is not well understood. Here, we …