A unique and innovative analysis of how social media can affect the spread of a disease has been designed and implemented by a scientist at Penn State University studying attitudes toward the H1N1 vaccine. Marcel Salath, an assistant professor of biology, studied how users of Twitter -- a popular microblogging and social-networking service -- expressed their sentiments about a new vaccine. He then tracked how the users' attitudes correlated with vaccination rates and how microbloggers with the same negative or positive feelings seemed to influence others in their social circles. The research is considered the first case study in how social-media sites affect and reflect disease networks, and the method is expected to be repeated in the study of other diseases. The results will be published in the journal PLoS Computational Biology.
Salath explained that he chose Twitter for two reasons. First, unlike the contents of Facebook, Twitter messages, known as "tweets," are considered public data and anyone can "follow," or track, the tweets of anyone else. "People tweet because they want other members of the public to hear what they have to say," Salath said. Second, Twitter is the perfect database for learning about people's sentiments. "Tweets are very short -- a maximum of 140 characters," Salath explained. "So users have to express their opinions and beliefs about a particular subject very concisely." Salath began by amassing 477,768 tweets with vaccination-related keywords and phrases. He then tracked users' sentiments about a particular new vaccine for combating H1N1 -- a virus strain responsible for swine flu. The collection process began in August 2009, when news of the new vaccine first was made public, and continued through January 2010.
Salath explained that sorting through the enormous number of vaccination-related tweets was no simple matter. First, he partitioned a random subset of about 10 percent and asked Penn State studen
|Contact: Barbara Kennedy|