LMFAO! Humor as a Response to Fear: Decomposing Fear Control within the Extended Parallel Process Model

Abstract

This study seeks to analyze fear control responses to the 2012 Tips from Former Smokers campaign using the Extended Parallel Process Model (EPPM). The goal is to examine the occurrence of ancillary fear control responses, like humor. In order to explore individuals’ responses in an organic setting, we use Twitter data—tweets—collected via the Firehose. Content analysis of relevant fear control tweets (N = 14,281) validated the existence of boomerang responses within the EPPM: denial, defensive avoidance, and reactance. More importantly, results showed that humor tweets were not only a significant occurrence but constituted the majority of fear control responses.

Funding

Research reported in this publication was supported by the Centers for Disease Control and Prevention and National Cancer Institute of the National Institutes of Health under Award Number U01CA154254. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.

Notes

1. The Tips campaign was also re-launched in 2013–2017.

2. Only tweets from account users who have a public account (support.twitter.com) can be fetched. However, about 92% of users share their tweets with everyone (Meeder, Tam, Kelley, & Cranor, 2009).

^3. Byrne and Hart (2009) also note that selective exposure is a boomerang mechanism that can occur as consequence of exposure to fear, but it has not been validated in the literature (as a fear control response).

^4. Severity (e.g., how harmful smoking is) and susceptibility (e.g., whether I am at risk of throat cancer) are treated in an additive manner (Witte, 1998).

^5. Message efficacy (e.g., help provided in this quit line) and self-efficacy (e.g., I am able to quit smoking) are treated in an additive manner (Witte, 1998).

^6. Fear control responses are sometimes named differently. For instance, reactance is also named perceived manipulation; denial is also named issue derogation (Witte, Berkowitz, Cameron, & McKeon, 1998).

^7. Twitter user names have all been redacted.

^8. Tweets have not been edited and are hence shown verbatim throughout.

^9. Many of the quotes in her study refer to laughter by those watching the ads (Wolburg, 2006, pp. 306, 308, 314).

^10. Freud borrowed the idea that the purpose of laughter is to release excess nervous energy from Herbert Spencer (1860).

^11. Twitter’s API samples from the Firehose. API sampling varies anywhere from 1–60% of Twitter content (https://dev.twitter.com/docs/streaming-apis).

^12. A standardized code set was constructed and eight human coders were paired into four coding teams to classify a random sample (N = 1,400; 350 tweets per dyad) of the Tips-relevant tweets (N = 193,491) for message acceptance, rejection, or disregard. Intercoder reliability for content coding was acceptable (K = .75). This code set was then used to train the naïve Bayes classifier to machine classify the corpus of Tips-relevant tweets.

^13. The relevant Tips tweets are the population of 193,491 tweets.

^14. r is the effect size (Rosnow & Rosenthal, 1996). Small ≤ .1, medium > .1 ≤ .5, large > .5.

Additional information

Funding

Research reported in this publication was supported by the Centers for Disease Control and Prevention and National Cancer Institute of the National Institutes of Health under Award Number U01CA154254. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.

Notes on contributors

Eulàlia P. Abril

Eulàlia P. Abril (Ph.D., University of Wisconsin-Madison) is an assistant professor of Communication at the University of Illinois at Chicago. Her research areas include health and political communication, new media effects, persuasion, and public opinion.

Glen Szczypka

Glen Szczypka (M.A., DePaul University) is the Deputy Director of the Health Media Collaboratory and Principal Research Scientist at NORC at the University of Chicago. He is a Senior Consultant for the CDC's Office on Smoking and Health and has over 15 years of experience working with government and nonprofits to evaluate and measure the effectiveness of public health campaigns.

Sherry L. Emery

Sherry L. Emery (Ph.D., University of North Carolina at Chapel Hill) is the Director, of the Health Media Collaboratory and Senior Fellow at NORC at the University of Chicago. Her research has focused on tobacco-related media campaign evaluation, social media measurement and analysis, tobacco marketing, and tobacco control policy.