Published on June 4, 2019
For a technical audience of engineers, quantitative data often holds the key to persuasion. For more general audiences, however, narrative or storytelling has been shown to potentially hold greater sway. In addition, the effectiveness of both techniques is context-based and contingent on the type of response one might induce.
Research on both modes has typically examined the two modes in isolation, comparing their effectiveness in persuasion. But they are not mutually exclusive techniques, and can be put to use together in shaping a persuasive argument, particularly in fields such as health communication. Hai Tran, an Associate Professor in DePaul’s College of Communication, will reconceptualize the two techniques as distinct yet compatible with one another in an upcoming presentation at ProComm 2019 in Aachen, Germany.
Narrative is thought to make stronger bonds with your audience. Using elements such as anecdotes, quotes, testimonials provides real-life examples for readers and listeners that are easier to connect with. Quantitative data, on the other hand, is valued for their objective, verifiable representative of reality. But as Tran points out, Seymour Epstein’s cognitive-experiential theory suggests that people use two distinct systems when processing information: a rational one and an experiential one. These two systems are not mutually exclusive, and though one might dominate at a certain time, they are thought to work simultaneously, and in parallel.
Statistical evidence and narrative induce different responses and have different impacts. So, why not use both, rather than one or the other? Find out how to take advantage of both of these modes of communication in Aachen this summer, or return to this page after the conference for more information!
Hai L. Tran (Ph.D.) is an Associate Professor at DePaul University (USA), where he teaches multimedia storytelling and data reporting. His research focuses on communication technology, including multimedia effects, online agenda setting, and research methodology.