BackgroundThis paper aims to synthesise the literature on machine learning (ML) and big
data applications for mental health, highlighting current research and applications in …

Organizations' increasing reliance on externally produced information, such as online user-
generated content (UGC) and crowdsourcing, challenges common assumptions about …

Background State child welfare agencies collect, store, and manage vast amounts of data.
However, they often do not have the right data, or the data is problematic or difficult to inform …

Objective: Child welfare agencies often lack information about the front-end service needs of
the families they serve. Thus, the current study tests the feasibility of text mining and …

Background Research on child protective services (CPS) is impeded by a lack of high-
quality structured data. Crucial information on cases is often documented in case files, but …

With the growth of machine learning and other computationally intensive techniques for
analyzing data, new opportunities emerge to repurpose organizational information sources …

It is now evident that Big Data has pinched immense contemplation from scientists in data
sciences, strategy and chiefs in governments and activities. As the speed of data progress …

Objective This paper aims to synthesise the literature on machine learning (ML) and big data
applications for mental health, highlighting current research and applications in practice …

Data collected by organizations is typically used for tactical purposes–solving a business
need. In this study we show the relationship between inferential utility and institutional …