Whose Advantage? Measuring Attention Dynamics across YouTube and Twitter on Controversial Topics
Whose Advantage? Measuring Attention Dynamics across YouTube and Twitter on Controversial Topics
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DOI：
10.48550/arxiv.2204.00988
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发表时间：
2022-04
期刊：
影响因子：
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通讯作者：
Jooyoung Lee;Siqi Wu;A. Ertugrul;Yu-Ru Lin;Lexing Xie
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文献类型：
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作者：
Jooyoung Lee;Siqi Wu;A. Ertugrul;Yu-Ru Lin;Lexing Xie
这种意识形态的不对称性最近在有争议的网络空间中被观察到，在这些领域，保守派的声音似乎相对更明显，尽管众所周知，自由派在数字平台上拥有人口优势。然而，之前的大多数研究要么集中在一个单一的平台上，要么集中在一个单一的政治话题上。一个意识形态群体是否会在平台和/或话题上获得更多关注，以及注意力动态是如何随着时间的推移而演变的，还没有得到探索。在这项工作中，我们提出了一项量化研究，将两个社交平台--YouTube和Twitter--的集体关注联系起来，集中在围绕三个有争议的政治话题的热门视频的在线活动上，这些视频包括堕胎、枪支控制和黑人生命也是16个月。我们提出了几套以视频为中心的衡量标准，以表征不同意识形态群体的在线注意力积累情况。我们发现，双方都不是在连胜：总体上，与右倾视频相比，左倾视频的浏览量更多，更吸引人，但推特上的帖子更少。左倾视频的注意力时间序列展开得更快，但右倾视频的时间跨度更长。对早期采用者和推特层叠的网络分析表明，左倾视频的信息扩散往往涉及集中的参与者，而右倾视频的信息扩散在注意力生命周期中开始得更早。总而言之，我们的发现超越了数字空间中意识形态不对称的静态图景，并提供了一套量化不同社交平台注意力动态的方法。
The ideological asymmetries have been recently observed in contested online spaces, where conservative voices seem to be relatively more pronounced even though liberals are known to have the population advantage on digital platforms. Most prior research, however, focused on either one single platform or one single political topic. Whether an ideological group garners more attention across platforms and/or topics, and how the attention dynamics evolve over time, have not been explored. In this work, we present a quantitative study that links collective attention across two social platforms -- YouTube and Twitter, centered on online activities surrounding popular videos of three controversial political topics including Abortion, Gun control, and Black Lives Matter over 16 months. We propose several sets of video-centric metrics to characterize how online attention is accumulated for different ideological groups. We find that neither side is on a winning streak: left-leaning videos are overall more viewed, more engaging, but less tweeted than right-leaning videos. The attention time series unfold quicker for left-leaning videos, but span a longer time for right-leaning videos. Network analysis on the early adopters and tweet cascades show that the information diffusion for left-leaning videos tends to involve centralized actors; while that for right-leaning videos starts earlier in the attention lifecycle. In sum, our findings go beyond the static picture of ideological asymmetries in digital spaces and provide a set of methods to quantify attention dynamics across different social platforms.