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On Twitter, Anti-vaccination Sentiments Spread More Easily than Pro-vaccination Sentiments
Posted By Adan On April 5, 2013 @ 12:25 pm In Medical Tyranny,Old Infowars Posts Style,Tile | Comments Disabled
April 5, 2013
On Twitter, a popular microblogging and social-networking service, statements about vaccines may have unexpected effects—positive messages may backfire, according to a team of Penn State University researchers led by Marcel Salathé, an assistant professor of biology. The team tracked the 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 influenza H1N1—a virus strain responsible for swine flu. The results, which may help health officials improve strategies for vaccination-awareness efforts, will be published in the journal EPJ Data Science on 4 April 2013.
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. For example, a tweet expressing a desire to get the H1N1 vaccine would be considered positive, while a tweet expressing the belief that the vaccine causes harm would be considered negative. A tweet concerning a different vaccine; for example, the Hepatitis B vaccine, would be considered irrelevant.
Next, the team used the students’ ratings to design a computer algorithm for cataloging the remaining 90 percent of the tweets according to the sentiments they expressed. “The human-rated tweets served as a ‘learning set’ that we used to ‘teach’ the computer how to rate the tweets accurately,” Salathé explained. After the tweets were analyzed by the computer algorithm, the final tally was 318,379 tweets expressing either positive, negative, or neutral sentiments about the H1N1 vaccine.
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