关键词
机器学习、YouTube、社交媒体、推荐系统、两极分化、交流
摘要
社交网络已经建立了一种沟通和理解社会关系的新方式。反过来,在可以认为是负面的影响中,算法已经在广泛的猜想和关于其指导和协调公众舆论的能力的不同立场的保护下被构建和开发。本文从逆向工程和语义挖掘的过程中,对 YouTube 推荐系统进行分析。通过这种方式,首先,为了概述一个关键结果,从一开始就分析的主题并不趋于极端。接下来,通过对所选主题的研究,结果并没有为所提出的假设提供明确的解决方案,因为正如在类似文章中所显示的那样,形成推荐系统的因素是多种多样的,而且性质非常多样化。 结果表明,所分析的所有主题的两极分化内容并不相同,这可能表明存在改变变量之间关系的博主(或公司的行为)。另一个贡献是确认我们正在处理非线性但可能系统化的过程。尽管如此,目前的工作为进一步对该主题进行学术研究打开了大门,以澄清这些算法在我们社会中的作用的未知数。
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技术信息
收到: 30-05-2022
修订: 21-06-2022
公认: 13-07-2022
OnlineFirst: 30-10-2022
发布日期: 01-01-2023
文章修改时间: 22 天 | 期刊编号的平均时间修订 74: 40 天
文章接受时间: 44 天 | 期刊编号的平均接受时间 74: 69 天
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文章编辑时间: 216 天 | 期刊编号的平均编辑时间 74: 239 天
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被引用
引述 Web of Science
Barroso-Moreno, C; del Fresno-Garcia, M and Rayon-Rumayor, L. Inclusive employability and the role of social networks in digital society. A case study on Twitter, Instagram and YouTube Barroso-Moreno, C; del Fresno-Garcia, M and Rayon-Rumayor, L REVISTA ICONO 14-REVISTA CIENTIFICA DE COMUNICACION Y TECNOLOGIAS, 2023.
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如何引用
García-Marín, J., & Serrano-Contreras, I. (2023). (Un)founded fear towards the algorithm: YouTube recommendations and polarisation. [Miedo (in)fundado al algoritmo: Las recomendaciones de YouTube y la polarización]. Comunicar, 74, 61-70. https://doi.org/10.3916/C74-2023-05