认知网络科学对网络社会认知的研究进展
Cognitive network science for understanding online social cognitions: A brief review
摘要：
社交媒体正在将大量用户在时间线和情感内容方面的认知数字化。这些大数据为研究感知、个性和信息扩散等认知现象提供了前所未有的机会，但需要合适的可解释框架。由于社交媒体数据来自用户的头脑，因此这一挑战的有价值的候选者是认知网络，即为心理概念联想提供结构的认知模型。这项工作概述了认知网络科学如何通过在线媒体为理解认知开辟新的定量方法，例如：（i）重建用户如何使用机器学习无法获得的上下文知识在语义和情感上构建事件，（ii）通过社会话语中的知识结构研究概念突显/突出;（iii）通过帖子中的语言研究用户的个性特征，如开放性、好奇心和创造力;（iv）通过比较影响者和追随者的心态的多层网络，将认知/情感内容和社会动态联系起来。这些进步结合了认知、网络和计算机科学，以理解数字和现实世界环境中的认知机制，但在代表性、个体差异性和数据整合方面存在局限性。这些方面的讨论沿着操纵社会认知数据的伦理影响。在未来，通过网络和社交媒体阅读认知可以暴露被在线平台放大的认知偏见，并为政策制定、教育和市场提供有关大规模复杂认知趋势的相关信息。
英文摘要：
Social media are digitalising massive amounts of users' cognitions in terms of timelines and emotional content. Such Big Data opens unprecedented opportunities for investigating cognitive phenomena like perception, personality and information diffusion but requires suitable interpretable frameworks. Since social media data come from users' minds, worthy candidates for this challenge are cognitive networks, models of cognition giving structure to mental conceptual associations. This work outlines how cognitive network science can open new, quantitative ways for understanding cognition through online media, like: (i) reconstructing how users semantically and emotionally frame events with contextual knowledge unavailable to machine learning, (ii) investigating conceptual salience/prominence through knowledge structure in social discourse; (iii) studying users' personality traits like openness-to-experience, curiosity, and creativity through language in posts; (iv) bridging cognitive/emotional content and social dynamics via multilayer networks comparing the mindsets of influencers and followers. These advancements combine cognitive-, network- and computer science to understand cognitive mechanisms in both digital and real-world settings but come with limitations concerning representativeness, individual variability and data integration. Such aspects are discussed along the ethical implications of manipulating socio-cognitive data. In the future, reading cognitions through networks and social media can expose cognitive biases amplified by online platforms and relevantly inform policy making, education and markets about massive, complex cognitive trends.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
