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推文和 YouTube 评论有何共同之处？对与 2020 年美国大选相关数据的情感和图分析。

What Tweets and YouTube comments have in common? Sentiment and graph analysis on data related to US elections 2020.

机构信息

Institute of Computer Science, Foundation for Research and Technology, Vassilika Vouton, Heraklion, Crete, Greece.

Computer Science Department - University of Crete, Voutes Campus, Heraklion, Crete, Greece.

出版信息

PLoS One. 2023 Jan 31;18(1):e0270542. doi: 10.1371/journal.pone.0270542. eCollection 2023.

DOI:10.1371/journal.pone.0270542
PMID:36719868
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9888715/
Abstract

Most studies analyzing political traffic on Social Networks focus on a single platform, while campaigns and reactions to political events produce interactions across different social media. Ignoring such cross-platform traffic may lead to analytical errors, missing important interactions across social media that e.g. explain the cause of trending or viral discussions. This work links Twitter and YouTube social networks using cross-postings of video URLs on Twitter to discover the main tendencies and preferences of the electorate, distinguish users and communities' favouritism towards an ideology or candidate, study the sentiment towards candidates and political events, and measure political homophily. This study shows that Twitter communities correlate with YouTube comment communities: that is, Twitter users belonging to the same community in the Retweet graph tend to post YouTube video links with comments from YouTube users belonging to the same community in the YouTube Comment graph. Specifically, we identify Twitter and YouTube communities, we measure their similarity and differences and show the interactions and the correlation between the largest communities on YouTube and Twitter. To achieve that, we have gather a dataset of approximately 20M tweets and the comments of 29K YouTube videos; we present the volume, the sentiment, and the communities formed in YouTube and Twitter graphs, and publish a representative sample of the dataset, as allowed by the corresponding Twitter policy restrictions.

摘要

大多数分析社交网络中政治流量的研究都集中在单一平台上，而政治事件的活动和反应则会在不同的社交媒体上产生互动。忽略这种跨平台的流量可能会导致分析错误，错过社交媒体之间的重要互动，例如解释热门话题或病毒式讨论的原因。这项工作通过在 Twitter 上交叉发布视频 URL 将 Twitter 和 YouTube 社交网络联系起来，以发现选民的主要趋势和偏好，区分用户和社区对某种意识形态或候选人的偏好，研究对候选人的情绪以及衡量政治同质性。这项研究表明，Twitter 社区与 YouTube 评论社区相关联：即，在转发图中属于同一社区的 Twitter 用户倾向于发布带有来自 YouTube 评论图中同一社区的 YouTube 用户评论的视频链接。具体来说，我们确定了 Twitter 和 YouTube 社区，衡量了它们的相似性和差异性，并展示了 YouTube 和 Twitter 上最大社区之间的交互和相关性。为此，我们收集了大约 2000 万条推文和 29000 个 YouTube 视频评论的数据；我们展示了在 YouTube 和 Twitter 图中形成的社区的数量、情绪和社区，并发布了数据集的代表性样本，这是符合相应的 Twitter 政策限制的。

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