Components of human decisions to share information

人类共享信息决策的组成部分

• 批准号: RGPIN-2021-03438
• 负责人: Dore, Bruce
• 金额: $ 2.04万
• 依托单位: McGill University
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2021
• 资助国家: 加拿大
• 起止时间: 2021-01-01 至 2022-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=741961
• 关键词: Components; human; decisions; share; information

Sharing information with others is a central part of human life. Although people decide to share as individuals, consistencies in the factors driving sharing decisions can evoke cascades of sharing that cause content to spread rapidly through a population. Recently, considerable public attention has been paid to the rapid spread of content via online networks. However, the neurobiological origins of such widespread information sharing are still unclear. The long-term vision for the proposed research program is to address the following questions: What is the cognitive and neural architecture that supports human decisions to influence others, and how can we design information environments to effectively shape these decisions? Beyond advancing our basic science understanding of a fundamental human behaviour, this work will generate models of informational influence with relevance extending beyond psychology and neuroscience to fields like marketing, information technology, public health, and political science. In the next five years, I plan to take the first steps to tackle the research question by investigating how patterns of brain activity, psychological processes, and information content features predict decisions to share informative and persuasive messages. Two PhD students and 5 undergraduate research assistants will be hired under this interdisciplinary research program. Together, we will develop frameworks for i) identifying brain patterns that are highly predictive of individual and population-level information sharing, ii) situating these brain patterns within causal models in order to advance theory, and iii) asking whether brain signals are uniquely able to capture signatures of information sharing behaviours, or if these outcomes can also be predicted on the basis of objective content features and subjective evaluations. Under my supervision, these students will be trained on a highly interdisciplinary set of techniques, including online and laboratory experimentation, computational analysis of unstructured text and image data, and multivariate analysis of neuroimaging data. The output from the proposed research will be crucial for scientists, policymakers, and business leaders interested in knowing what causes content to spread through offline and online networks, and what they can do to help control this spread. The unique combination of data sources, combined with the innovative and modern approach to analysis, will allow us to make critical scientific advances. Overall, the intent with this work is to develop a more complete theory of information sharing that effectively links basic neurobiological processes to large-scale behavioural outcomes in populations.

与他人共享信息是人类生活的核心部分。尽管人们决定以个人身份进行共享，但驱动共享决策的因素的一致性可能会引发级联共享，从而导致内容在人群​​中快速传播。最近，通过在线网络快速传播的内容受到了公众的广泛关注。然而，如此广泛的信息共享的神经生物学起源仍不清楚。 拟议研究计划的长期愿景是解决以下问题：支持人类决策影响他人的认知和神经架构是什么？我们如何设计信息环境来有效塑造这些决策？除了增进我们对人类基本行为的基础科学理解之外，这项工作还将生成信息影响模型，其相关性超越心理学和神经科学，扩展到营销、信息技术、公共卫生和政治学等领域。在接下来的五年中，我计划通过调查大脑活动模式、心理过程和信息内容特征如何预测分享信息丰富和有说服力的信息的决策来解决这个研究问题。该跨学科研究项目将聘用两名博士生和五名本科生研究助理。我们将共同开发框架：i）识别高度预测个人和群体信息共享的大脑模式，ii）将这些大脑模式置于因果模型中以推进理论，以及iii）询问大脑信号是否具有独特的能力捕获信息共享行为的特征，或者是否也可以根据客观内容特征和主观评价来预测这些结果。在我的监督下，这些学生将接受一套高度跨学科的技术培训，包括在线和实验室实验、非结构化文本和图像数据的计算分析以及神经影像数据的多元分析。 对于有兴趣了解内容通过离线和在线网络传播的原因以及他们可以采取哪些措施来帮助控制这种传播的科学家、政策制定者和商界领袖来说，拟议研究的结果至关重要。数据源的独特组合，加上创新的现代分析方法，将使我们能够取得关键的科学进步。总的来说，这项工作的目的是开发一种更完整的信息共享理论，有效地将基本的神经生物学过程与人群的大规模行为结果联系起来。