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The Information-Attention Tradeoff: Toward an Understanding of the Fundamentals of Online Attention

The Information-Attention Tradeoff: Toward an Understanding of the Fundamentals of Online Attention
信息与注意力的权衡:了解在线注意力的基本原理
批准号:
2343858
负责人:
Marta Serra-Garcia
金额:
$39.99万
依托单位国家:
美国
项目类别:
Continuing Grant
财政年份:
2024
资助国家:
美国
项目状态:
未结题
起止时间:
2024-03-15 至 2027-02-28

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中文摘要
翻译
互联网和社交媒体作为绝大多数美国成年人的信息来源发挥着至关重要的作用。然而,在线平台不仅仅是信息空间。它们是竞争的竞技场,追求点击量和观点,这可能会导致不准确信息的传播。这项研究提供了新的证据,有助于一场日益重要的政策辩论:我们如何在降低其风险的同时利用数字时代的优势?通过研究数字内容是如何构思以吸引受众,以及用户如何在这些领域分配他们的注意力,这项研究增强了我们对在线注意力的基本原理的理解。这些见解被用来测试在不影响内容吸引力的情况下增强内容信息价值的各种策略。这项研究通过开发一种新的、可扩展的实验范式,将现场实验数据和实验室实验数据相结合,推动了信息传播和人类注意力的研究。这个范式扩展了现有的基于发送者-接收者博弈的范式,产生了一种研究在线注意力和信息的新的方法论方法。这项研究将行为数据与文本分析和机器学习技术相结合,以全面评估信息提供者和消费者之间互动的多方面影响。使用实验数据,该项目测试干预措施,并开发一个理论框架来阐明注意力被捕获和分配的机制,最终塑造结果的信息传输。这一奖项反映了NSF的法定使命,并通过使用基金会的智力优势和更广泛的影响审查标准进行评估,被认为值得支持。
英文摘要
The internet and social media play a critical role as information sources for a large majority of US adults. However, online platforms are not just informative spaces. They are competitive arenas that pursue clicks and views, which could lead to the spread of inaccurate information. This research provides new evidence that contributes to an increasingly important policy debate: how can we harness the advantages of the digital era while mitigating its risks? By examining how digital content is crafted to captivate audiences and how users allocate their attention in such domains, this research enhances our understanding of the fundamentals of online attention. These insights are used to test various strategies to enhance the informational value of content without compromising its appeal. The resulting findings will provide insights into the impact of social media on information dissemination in society.This research advances the study of information transmission and human attention, by developing a new, scalable experimental paradigm that combines field and lab experimental data. This paradigm expands existing paradigms based on sender-receiver games, resulting in a new methodological approach to study online attention and information. The proposed research combines behavioral data with text analysis and machine learning techniques, to comprehensively assess the multifaceted effects of the interaction between suppliers and consumers of information. Using the experimental data, the project tests interventions and develops a theoretical framework to elucidate the mechanisms by which attention is captured and allocated, ultimately shaping the resulting information transmission.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
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