HealthSocialytics is an ongoing project at UC Riverside. Our goal is to bring the power of health-related social and news big data to the user’s fingertips through a suite of Web tools.
We are continuously monitoring and analyzing data from social networks, forums and news feeds, and we provide intuitive visualization tools to interactively explore various dimensions of this massive information.
A tool to view, analyze and predict real-time social and news chatter related to health. The data comes from three sources:
a. Social Networks like Twitter - only health-related posts are considered
b. Health Forums - we are collecting data from dozen of Web forum sites
c. News - only health-related news are considered
The values for the next few days of various features of social and news chatter are predicted using state-of-art prediction models. For instance, the system predicts the number of users that are expected to talk about a specific disorder or drug in the next days.
The Twitter co-occurrence graph shows the most popular terms in posts about the query term (e.g. "flu"), where a link is added between two terms if they appear together in many posts.
Not all keywords are indexed in Twitter and News. We provide an autocomplete functionality to easily view which keywords are available.
Your feedback or suggestions are always welcome. Please email us here.
Professor Vagelis Hristidis
Moloud Shahbazi, PhD Candidate
Michael Brevard, Undergraduate
Shiwen Cheng, PhD Candidate
Eduardo Ruiz, PhD, Alumnus