Characters matter: how narratives shape affective responses to risk communication

Introduction

Whereas scientists depend on the language of probability to relay information about hazards, risk communication may be more effective when embedding scientific information in narratives. The persuasive power of narratives is theorized to reside, in part, in narrative transportation.

Purpose

This study seeks to advance the science of stories in risk communication by measuring real-time affective responses as a proxy indicator for narrative transportation during science messages that present scientific information in the context of narrative.

Methods

This study employed a within-subjects design in which participants (n = 90) were exposed to eight science messages regarding flood risk. Conventional science messages using probability and certainty language represented two conditions. The remaining six conditions were narrative science messages that embedded the two conventional science messages within three story forms that manipulated the narrative mechanism of character selection. Informed by the Narrative Policy Framework, the characters portrayed in the narrative science messages were hero, victim, and victim-to-hero. Natural language processing techniques were applied to identify and rank hero and victim vocabularies from 45 resident interviews conducted in the study area; the resulting classified vocabulary was used to build each of the three story types. Affective response data were collected over 12 group sessions across three flood-prone communities in Montana. Dial response technology was used to capture continuous, second-by-second recording of participants’ affective responses while listening to each of the eight science messages. Message order was randomized across sessions. ANOVA and three linear mixed-effects models were estimated to test our predictions.

Results

First, both probabilistic and certainty science language evoked negative affective responses with no statistical differences between them. Second, narrative science messages were associated with greater variance in affective responses than conventional science messages. Third, when characters are in action, variation in the narrative mechanism of character selection leads to significantly different affective responses. Hero and victim-to-hero characters elicit positive affective responses, while victim characters produce a slightly negative response.

Conclusions

In risk communication, characters matter in audience experience of narrative transportation as measured by affective responses.

引言
尽管科学家们依赖概率语言来传递灾害相关信息，但在风险沟通中，将科学信息嵌入叙事文本往往能提升沟通效果。叙事的说服效力，其部分理论来源为叙事沉浸（narrative transportation）。

研究目的
本研究旨在推动风险沟通中的叙事科学发展，具体方式为：在以叙事为载体呈现科学信息的科学传播文本中，通过测量实时情感反应作为叙事沉浸的代理指标。

研究方法
本研究采用被试内实验设计，共招募90名参与者，让其接触8篇关于洪水风险的科学传播文本。其中，采用概率与确定性表述的常规科学传播文本共2种实验条件；剩余6种条件为叙事型科学传播文本，即将2篇常规科学传播文本嵌入3种故事框架中，这3种框架通过操控角色选择的叙事机制进行差异化设置。
本研究基于叙事政策框架（Narrative Policy Framework），将叙事型科学传播文本中的角色设定为三类：英雄角色、受害者角色以及从受害者转变为英雄的角色。研究人员借助自然语言处理（Natural Language Processing, NLP）技术，从研究区域开展的45份居民访谈文本中识别并排序出英雄与受害者相关词汇；基于分类得到的词汇表构建了上述三类故事框架。研究在蒙大拿州的3个易受洪水侵袭的社区开展，共完成12组实验场次，收集参与者的情感反应数据。
研究采用表盘反应技术（dial response technology）实时记录参与者收听8篇科学传播文本时的情感反应，记录精度为每秒一次。各场次实验中，科学传播文本的呈现顺序均经过随机化处理。本研究采用方差分析（ANOVA）与3个线性混合效应模型对研究假设进行检验。

研究结果
研究结果如下：其一，采用概率表述与确定性表述的科学语言均会引发负向情感反应，且二者间无统计学差异；其二，相较于常规科学传播文本，叙事型科学传播文本引发的情感反应方差更大；其三，当角色处于行动状态时，角色选择的叙事机制差异会导致参与者产生显著不同的情感反应：英雄角色与从受害者转变为英雄的角色会引发正向情感反应，而受害者角色则会引发轻微的负向情感反应。

结论
本研究结论显示，在风险沟通场景下，以情感反应为衡量指标的叙事沉浸体验中，角色设置对受众体验至关重要。