Forecasts have traditionally served as the basis for planning and executing supply chain
activities. Forecasts drive supply chain decisions, and they have become critically important …

Background The popularity and proliferation of online social networks (OSNs) have created
massive social interaction among users that generate an extensive amount of data. An OSN …

Social computing systems such as Twitter present new research sites that have provided
billions of data points to researchers. However, the availability of public social media data …

We present a machine learning-based methodology capable of providing real-time
(“nowcast”) and forecast estimates of influenza activity in the US by leveraging data from …

Several messages express opinions about events, products, and services, political views or
even their author's emotional state and mood. Sentiment analysis has been used in several …

Social media have been proposed as a data source for influenza surveillance because they
have the potential to offer real-time access to millions of short, geographically localized …

Traditional mental health studies rely on information primarily collected through personal
contact with a health care professional. Recent work has shown the utility of social media …

By aggregating self-reported health statuses across millions of users, we seek to
characterize the variety of health information discussed in Twitter. We describe a topic …

Today's societies are connected to a level that has never been seen before. The COVID-19
pandemic has exposed the vulnerabilities of such an unprecedently connected world. As of …

Accurate disease forecasts are imperative when preparing for influenza epidemic outbreaks;
nevertheless, these forecasts are often limited by the time required to collect new, accurate …