Stories vs Statistics: Which is better for memory?

Thomas Graeber, Christopher Roth and Florian Zimmermann in this voxeu post:

Widespread misperceptions shape attitudes on key societal topics, such as climate change and the recent pandemic. These belief distortions are puzzling in contexts where accurate statistical information is broadly available and attended to. This column argues that the nature of human memory may be key for understanding the persistence of misperceptions in practice. It documents that anecdotal information in the form of stories comes to mind more easily than statistical information, generating the potential for systematic belief biases.

Not surprised to read this. who remembers statistics?

Why do stories tend to stick, while statistics tend to be more rapidly forgotten? To make progress on this question, we start with a simple formal framework that builds on models that conceptualise the cue-dependent nature of episodic memory (Bordalo et al. 2021, 2023). Experiences such as the consumption of stories and statistics are stored as memory traces that are connected through associations. Recall of these traces is triggered by contextual cues. The key drivers of recall are similarity and interference. The higher the similarity between a memory trace and a cue, the more likely successful retrieval becomes. A higher number of non-target memory traces that are similar to the target trace weakens recall, as these non-target traces interfere with the successful retrieval of the target trace.

The model can account for the story-statistic gap. The reason stories stick according to our model is that the rich, contextualised information contained in stories makes them distinct from non-target memory traces. As a consequence, they suffer less from interference.

In tailored mechanism experiments, we test some of the core predictions of the model. The following insights emerge: First, the contextual features of stories give them an advantage over statistical information and cause the relatively high recall rates. This insight can be used to boost the long-run belief impact of statistics. Once contextual features are added to statistics, their recall rates improve. Second, in line with the principle of interference, the story-statistic gap increases in the total number of product scenarios participants are exposed to. Third, stories lose their edge over statistics in situations where participants are exposed to many similar stories that compete for retrieval.

Policy implications? Tell more stories:

Our results have ramifications for the effects of news coverage and mass media on belief formation. The mass media cover many topics not only by providing facts and statistics, but they frequently rely on anecdotes about individual cases that provide detailed qualitative, anecdotal information. For example, consider allegations about election fraud in the context of the 2020 US presidential election, where some outlets reported stories about individual instances of election fraud, even though these constituted rare exceptions.

Our results also bear implications for how policymakers, marketers, or leaders should communicate with their audiences: communication of statistical information can be greatly enhanced by complementing it with contextual anecdotes. For example, when discussing economic figures, it can be beneficial to provide anecdotes that are consistent with and relevant to the statistics being presented. Finally, our research also highlights the importance of timing in persuasion: statistics and facts are more effective when messaging is delivered close to the audience’s anticipated action, whereas stories are more effective when there is a delay involved.



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