How Big Data Analytics on Twitter Can Help Predict Disease Spread [VIDEO]
Social networks have become so common in our lives that we post everything on Facebook, Google+ or Twitter. As such we also post how we feel and if we feel sick. Researchers at the University of Rochester have now been able to use Twitter to predict how likely it is for a Twitter user to become sick. In the following video they show how they use Twitter to model how other factors — social status, exposure to pollution, interpersonal interaction and others — influence our health. The looked in total at 70 different factors and whether they had a positive, negative or neutral impact on the users’ health. They make predictions up to 8 days in advance what your health is going to be. With a 90% accuracy they are now able to predict if a Twitter user is going to be ill the next day and this information can help that user make decisions in their lives.
Mark van Rijmenam is Co-founder and CEO of Datafloq. Datafloq is the One-Stop Shop around Big Data. We are the number one Big Data platform connecting Data and People, connecting all stakeholders in the global Big Data market. Mark is a strategist who advises organisations on how to develop their big data strategies. As such, he is a well sought after speaker on this topic. His book “Think ...