Chipidza Wallace, Krewson Christopher, Gatto Nicole, Akbaripourdibazar Elmira, Gwanzura Tendai
Center for Information Systems and Technology, Claremont Graduate University, California, USA.
Political Science Department, Brigham Young University, Provo, Utah, USA.
Big Data Soc. 2022 Mar 9;9(1):20539517221076486. doi: 10.1177/20539517221076486. eCollection 2022 Jan.
In this exploratory study, we examine political polarization regarding the online discussion of the COVID-19 pandemic. We use data from Reddit to explore the differences in the topics emphasized by different subreddits according to political ideology. We also examine whether there are systematic differences in the credibility of sources shared by the subscribers of subreddits that vary by ideology, and in the tendency to share information from sources implicated in spreading COVID-19 misinformation. Our results show polarization in topics of discussion: the Trump, White House, and economic relief topics are statistically more prominent in liberal subreddits, and China and deaths topics are more prominent in conservative subreddits. There are also significant differences between liberal and conservative subreddits in their preferences for news sources. Liberal subreddits share and discuss articles from more credible news sources than conservative subreddits, and conservative subreddits are more likely than liberal subreddits to share articles from sites flagged for publishing COVID-19 misinformation.
在这项探索性研究中,我们考察了关于新冠疫情在线讨论的政治两极分化现象。我们使用来自Reddit的数据,以探究不同子版块根据政治意识形态所强调的话题差异。我们还考察了不同意识形态的子版块订阅者所分享来源的可信度,以及分享来自传播新冠疫情错误信息相关来源信息的倾向是否存在系统性差异。我们的研究结果显示了讨论话题的两极分化:“特朗普”“白宫”和“经济救助”话题在自由派子版块中在统计上更为突出,而“中国”和“死亡”话题在保守派子版块中更为突出。自由派和保守派子版块在对新闻来源的偏好上也存在显著差异。自由派子版块比保守派子版块分享和讨论来自更可信新闻来源的文章,并且保守派子版块比自由派子版块更有可能分享来自被标记为发布新冠疫情错误信息的网站的文章。