Social bots, or algorithmic agents that amplify certain viewpoints and interact with selected actors on social media, may influence online discussion, news attention, or even public opinion through coordinated action. Previous research has documented the presence of bot activities and developed detection algorithms. Yet, how social bots influence attention dynamics of the hybrid media system remains understudied. Leveraging a large collection of both tweets (N = 1,657,551) and news stories (N = 50,356) about the early COVID-19 pandemic, we employed bot detection techniques, structural topic modeling, and time series analysis to characterize the temporal associations between the topics Twitter bots tend to amplify and subsequent news coverage across the partisan spectrum. We found that bots represented 8.98% of total accounts, selectively promoted certain topics and predicted coverage aligned with partisan narratives. Our macro-level longitudinal description highlights the role of bots as algorithmic communicators and invites future research to explain micro-level causal mechanisms.

中文翻译：

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混合媒体系统中的算法代理：社交机器人、选择性放大和有关 COVID-19 的党派新闻

社交机器人或算法代理可以放大某些观点并在社交媒体上与选定的参与者互动，可能会通过协调行动影响在线讨论、新闻关注甚至公众舆论。以前的研究记录了机器人活动的存在并开发了检测算法。然而，社交机器人如何影响混合媒体系统的注意力动态仍有待研究。利用大量关于早期 COVID-19 大流行的推文 (N = 1,657,551) 和新闻报道 (N = 50,356)，我们采用机器人检测技术、结构主题建模和时间序列分析来表征主题之间的时间关联Twitter 机器人倾向于扩大和随后在党派范围内的新闻报道。我们发现机器人占总账户的 8.98%，有选择地宣传某些主题并预测与党派叙述一致的报道。我们的宏观纵向描述强调了机器人作为算法传播者的作用，并邀请未来的研究来解释微观层面的因果机制。