Although many Facebook users already have concerns regarding their privacy, the social network’s large user base combined with the vast amount of data available continues to motivate marketers and researchers to find new uses for the information. Now, the University of North Carolina’s Center for Infectious Diseases team is hopeful that they have found a way to extract Facebook data to successfully predict the likelihood that an individual is carrying a sexually transmitted disease (STD).
Dr. Peter Leone, who led the University of North Carolina research team, recently said the following regarding the team’s analysis of a recent syphilis outbreak:
“When we looked at the networks we could connect many of the cases to sexual encounters, and when we asked who they hung out with, who they knew, we could connect 80 percent of the cases.”
Leone, who stated that people in a similar social circle are more likely to sleep with one another, believes that the amplification online social networks provide compared to real-world social networks may eventually help prevent STD transmission and outbreaks.
While an app that is capable of analyzing Facebook data to determine the likelihood of an STD infection or outbreak seems far-fetched, a University of California professor has already created an app that analyzes newsfeed data to predict an individual’s risk of getting the flu on any given day. However, it is important to note all of the predictive health apps have limitations and are primarily based on user input. Since most Facebook users are highly unlikely to make an online reference to an STD or symptom and these diseases are spread differently than the common flu, an accurate predictive STD app could be extremely difficult to develop. In addition, the legal consequences of developing this type of app will likely prohibit the majority of companies from participating in its development.
Do you feel that predictive health apps provide value or are they just plain creepy? Would you use one?