词汇熟悉度对在线参与度和资金的预测效用。
The predictive utility of word familiarity for online engagements and funding.
机构信息
School of Journalism and Communication, University of Oregon, Eugene, OR 97403;
School of Communication, The Ohio State University, Columbus, OH 43210.
出版信息
Proc Natl Acad Sci U S A. 2021 May 4;118(18). doi: 10.1073/pnas.2026045118.
Metacognitive frameworks such as processing fluency often suggest people respond more favorably to simple and common language versus complex and technical language. It is easier for people to process information that is simple and nontechnical compared to complex information, therefore leading to more engagement with targets. In two studies covering 12 field samples (total = 1,064,533), we establish and replicate this simpler-is-better phenomenon by demonstrating people engage more with nontechnical language when giving their time and attention (e.g., simple online language tends to receive more social engagements). However, people respond to complex language when giving their money (e.g., complex language within charitable giving campaigns and grant abstracts tend to receive more money). This evidence suggests people engage with the heuristic of complex language differently depending on a time or money target. These results underscore language as a lens into social and psychological processes and computational methods to measure text patterns at scale.
元认知框架，如加工流畅性，通常表明人们更喜欢简单和常见的语言，而不是复杂和技术性的语言。与复杂的信息相比，人们更容易处理简单而非技术性的信息，因此更容易与目标产生共鸣。在两项涵盖 12 个实地样本的研究中（共 1064533 人），我们通过证明当人们投入时间和注意力时，他们会更多地与非技术性语言互动，从而验证并复制了这种简单更好的现象（例如，简单的在线语言往往会收到更多的社交互动）。然而，当人们花钱时，他们会对复杂的语言做出反应（例如，慈善捐赠活动和赠款摘要中的复杂语言往往会收到更多的钱）。这一证据表明，人们根据时间或金钱目标，对复杂语言的启发式理解方式不同。这些结果强调了语言作为一种洞察社会和心理过程的视角，以及大规模衡量文本模式的计算方法。
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