Vaccination-Related Tweets May Cut Both Ways

April 10, 2013
On Twitter, positive messages on vaccinations may backfire, according to researchers at Penn State University. The team tracked pro-vaccine and anti-vaccine messages to which Twitter users were exposed, and then observed how those users expressed their own sentiments about a new vaccine for combating the H1N1 influenza virus. The results were published in the journal EPJ Data Science.

On Twitter, positive messages on vaccinations may backfire, according to researchers at Penn State University. The team tracked pro-vaccine and anti-vaccine messages to which Twitter users were exposed, and then observed how those users expressed their own sentiments about a new vaccine for combating the H1N1 influenza virus. The results were published in the journal EPJ Data Science.

The researchers began by amassing all tweets with vaccination-related keywords and phrases during the 2009 H1N1 pandemic. They then tracked users' sentiments about the H1N1 vaccine. To sort through and categorize the tweets, Salathé's team asked Penn State students to rate a random subset of about 10 percent and them as positive, negative, neutral, or irrelevant.T he students' ratings were used to to design a computer algorithm for cataloging the remaining 90 percent of the tweets according to the sentiments they expressed. The final tally was 318,379 tweets expressing positive, negative, or neutral sentiments about the H1N1 vaccine.

After categorizing the tweets, the team developed a statistical model with information including the number of microbloggers each Twitter user was following, and recorded whether those followed microbloggers tended to tweet negatively or positively about the H1N1 vaccine. Also included in the model was the number of the negative or positive tweets each of the followed microbloggers sent out. Other measures included in the statistical model were each Twitter user's number of reciprocal users—how many pairs of microbloggers were following each other—and the history of followers' own negative and positive tweets.

The team's first unexpected finding was that exposure to negative sentiment was contagious, while exposure to positive sentiments was not. This suggests that negative opinions on vaccination may spread more easily than positive opinions, according to Marcel Salathé, who led the study.

The team's second unexpected finding was that microbloggers with more reciprocal Twitter relationships tended to be influenced differently depending on whether the vaccine sentiments of their connections were positive or negative. “We found that, in reciprocal microblogging relationships, negative sentiments were more socially contagious than positive sentiments,” Salathé said. “When a microblogger had a lot of reciprocal Twitter connections with users who expressed anti-vaccine sentiments, he tended to tweet even more anti-vaccine sentiments himself.” Yet the same did not hold true for microbloggers with reciprocal connections with users who expressed pro-vaccine sentiments; that is, pro-vaccine sentiments did not seem to encourage people to tweet more positive sentiments of their own.

Third, the team looked at the sheer volume of negative or positive tweets followers received independent of how many individuals the users followed. “Not surprisingly, we found that a high volume of negative tweets seemed to encourage people to tweet more negatively. But strangely, a high volume of positive tweets seemed to encourage people to tweet more negatively, too,” Salathé said. “In other words, pro-vaccine messages seemed to backfire when enough of them were received.”

Salathé hopes to design additional Twitter studies to test whether the same effects can be observed for sentiments expressed about other vaccines, as well as about other health issues such as antibiotic usage, dieting, and exercising.

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