Audience Impressions of Narrative Structures and Personal Language Style in Science Communication on Social Media

2025-02-07

AI Summary

This study investigates how narrative structure and personalized language in social media science communication affect public comprehension, engagement, and—critically—the perceived authority of scientists. Employing a mixed-methods design, it combines a reader experiment (N=217) using Likert-scale surveys and in-depth interviews to identify context-dependent audience preferences for embodied techniques (e.g., concrete cases, stepwise scaffolding, first-person narration), with an author-level A/B editing intervention (N=43) to validate a structured editorial support framework. Key contributions include: (1) the first empirical finding that 87% of readers prefer embodied techniques—but only conditionally, contingent on topic, platform, and audience; (2) the proposal of a “continuum-based” editorial framework that transcends binary stylistic choices (e.g., formal vs. informal), enabling synergistic optimization of communicative effectiveness and scientific authority preservation; and (3) evidence that 92% of scientists significantly increased editing confidence and proactively integrated personalized strategies when using this framework.

Technology Category

• Application Domains: Humanities & Computational Social Science
• Natural Language Processing: Sentiment Analysis, Stylistic Analysis, and Argument Mining
• Humans and AI: Interaction Techniques and Devices

Application Category

• Social Networks and Social Media: Computational social science
• User Modeling, Personalization and Recommendation: Accountability, Transparency, and Ethics for personalization
• Web Mining and Content Analysis: Bridging structured and unstructured data

Abstract

Science communication increases public interest in science by educating, engaging, and encouraging everyday people to participate in the sciences. But traditional science communication is often too formal and inaccessible for general audiences. However, there is a growing trend on social media to make it more approachable using three techniques: relatable examples to make explanations concrete, step-by-step walkthroughs to improve understanding, and personal language to drive engagement. These techniques are flashy and often garner more engagement from social media users, but the effectiveness of these techniques in actually explaining the science is unknown. Furthermore, many scientists struggle with adopting these science communication strategies for social media, fearing it might undermine their authority. We conduct a reader study to understand how these science communication techniques on social media affect readers' understanding and engagement of the science. We found that while most readers prefer these techniques, they had diverse preferences for when and where these techniques are used. With these findings, we conducted a writer study to understand how scientists' varying comfort levels with these strategies can be supported by presenting different structure and style options. We found that the side-by-side comparison of options helped writers make editorial decisions. Instead of adhering to one direction of science communication, writers explored a continuum of options which helped them identify which communication strategies they wanted to implement.

Problem

• Effectiveness of social media science communication techniques
• Scientists' comfort with adopting new communication styles
• Impact of narrative structures on audience engagement

Innovation

• Relatable examples enhance explanation clarity
• Step-by-step walkthroughs improve understanding
• Personal language drives audience engagement