重度用户未能陷入过滤泡沫:来自中国网络视频平台的证据

IF 1.9 3区 物理与天体物理 Q2 PHYSICS, MULTIDISCIPLINARY Frontiers in Physics Pub Date : 2024-09-04 DOI:10.3389/fphy.2024.1423851
Chenbo Fu, Qiushun Che, Zhanghao Li, Fengyan Yuan, Yong Min
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引用次数: 0

摘要

随着技术的进步,配备推荐算法的网络平台在为获取信息提供便利的同时,也带来了算法偏见,塑造了用户的行为规范和行为方式。过滤泡沫被认为是算法偏差的负面后果,意味着用户信息消费多样性的减少,引起了广泛关注。以往关于过滤泡沫的研究通常独立使用用户的自我报告或行为数据。然而,可能由于测量方法的不同,现有研究对平台上是否存在过滤泡沫存在争议。在我们的研究中,我们采用内容类别多样性来衡量过滤泡沫,并创新性地将参与者的自我报告数据和网站行为数据结合起来使用,考察了单一在线视频平台(Bilibili)上的过滤泡沫。我们对 337 名大学生进行了问卷调查,并在他们知情授权的情况下收集了 322324 条浏览记录,构成了研究分析的数据集。研究发现,Bilibli 上存在过滤气泡,当观看游戏视频的次数增加时,多样性就会减少。此外,我们还从人口统计学和用户行为的角度考虑了影响过滤泡沫的因素。在人口统计学方面,女性和非会员用户更容易陷入过滤泡沫。在用户行为方面,特征重要性分析结果表明,重度用户的信息消费多样性高于其他用户,活跃度和碎片化对过滤泡沫的形成都有影响,但方向不同。最后,我们讨论了出现这些结果的原因,并从理论上解释了网络平台上的重度用户和普通用户的过滤泡沫效应可能比我们想象的要低。我们的结论为理解过滤泡沫和平台管理提供了有价值的见解。
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Heavy users fail to fall into filter bubbles: evidence from a Chinese online video platform
Accelerated by technological advancements, while online platforms equipped with recommendation algorithms offer convenience to obtain information, it also brought algorithm bias, shaping the norms and behaviors of their users. The filter bubble, conceived as a negative consequence of algorithm bias, means the reduction of the diversity of users’ information consumption, garnering extensive attention. Previous research on filter bubbles typically used users’ self-reported or behavioral data independently. However, existing studies have disputed whether filter bubbles exist on the platform, possibly owing to variations in measurement methods. In our study, we took content category diversity to measure the filter bubbles and innovatively used a combination of participants’ self-reported and website behavioral data, examining filter bubbles on a single online video platform (Bilibili). We conducted a questionnaire survey among 337 college students and collected 3,22,324 browsing records with their informed authorization, constituting the dataset for research analysis. The existence of filter bubbles on Bilibli is found, such that diversity will decrease when viewing Game videos increases. Furthermore, we considered the factors that influence filter bubbles from the perspective of demographics and user behavior. In demographics, female and non-member users are more likely to be trapped in filter bubbles. In user behavior, results of feature importance analysis indicate that the diversity of information consumption of heavy users is higher than others, and both activity and fragmentation have an impact on the formation of filter bubbles, but in different directions. Finally, we discuss the reasons for these results and a theoretical explanation that the filter bubbles effect may be lower than we thought for both heavy and normal users on online platforms. Our conclusions provide valuable insights for understanding filter bubbles and platform management.
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来源期刊
Frontiers in Physics
Frontiers in Physics Mathematics-Mathematical Physics
CiteScore
4.50
自引率
6.50%
发文量
1215
审稿时长
12 weeks
期刊介绍: Frontiers in Physics publishes rigorously peer-reviewed research across the entire field, from experimental, to computational and theoretical physics. This multidisciplinary open-access journal is at the forefront of disseminating and communicating scientific knowledge and impactful discoveries to researchers, academics, engineers and the public worldwide.
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