In March 2012, the CDC launched "Tips from Former Smokers," a $54 million national campaign featuring individuals experiencing long-term health consequences of smoking. The campaign approach was based on strong evidence that anti-tobacco ads portraying fear, graphic images, and personal testimonials are associated with attitudinal and behavior change. Yet it was also controversial; critics cited the danger that viewers might reject such intensely graphic messages. Tasked with informing this debate, our study analyzes the corpus of Tips campaign-related tweets obtained via the Twitter Firehose. We provide a novel and rigorous method for media campaign evaluation within the framework of the Extended Parallel Process Model. Among the relevant Tweets, 87% showed evidence of message acceptance, while 7% exhibited message rejection.
Keywords: Anti-smoking; Big data; Extended Parallel Process Model; Tips; Twitter.