Ceron Wilson, Gruszynski Sanseverino Gabriela, de-Lima-Santos Mathias-Felipe, Quiles Marcos G
Federal University of Sao Paulo, Av. Cesare Mansueto Giulio Lattes, 1201 São José dos Campos, Brazil.
University of Toulouse III - Paul Sabatier, 115d Route De Narbonne, 31077 Toulouse Cedex 4, France.
Soc Netw Anal Min. 2021;11(1):47. doi: 10.1007/s13278-021-00753-z. Epub 2021 May 19.
Fact-checking verifies a multitude of claims and remains a promising solution to fight fake news. The spread of rumors, hoaxes, and conspiracy theories online is evident in times of crisis, when fake news ramped up across platforms, increasing fear and confusion among the population as seen in the COVID-19 pandemic. This article explores fact-checking initiatives in Latin America, using an original Markov-based computational method to cluster topics on tweets and identify their diffusion between different datasets. Drawing on a mixture of quantitative and qualitative methods, including time-series analysis, network analysis and in-depth close reading, our article proposes an in-depth tracing of COVID-related false information across the region, comparing if there is a pattern of behavior through the countries. We rely on the open Twitter application programming interface connection to gather data from public accounts of the six major fact-checking agencies in Latin America, namely Argentina (), Brazil (), Chile (), Colombia ( from ), Mexico ( from ) and Venezuela (). In total, these profiles account for 102,379 tweets that were collected between January and July 2020. Our study offers insights into the dynamics of online information dissemination beyond the national level and demonstrates how politics intertwine with the health crisis in this period. Our method is capable of clustering topics in a period of overabundance of information, as we fight not only a pandemic but also an infodemic, evidentiating opportunities to understand and slow the spread of false information.
事实核查验证了大量的说法,仍然是打击假新闻的一个有前景的解决方案。在危机时期,谣言、恶作剧和阴谋论在网上的传播很明显,比如在新冠疫情期间,假新闻在各个平台上激增,加剧了民众的恐惧和困惑。本文探讨拉丁美洲的事实核查举措,使用一种基于马尔可夫的原创计算方法对推文主题进行聚类,并识别它们在不同数据集之间的传播情况。本文采用定量和定性方法相结合的方式,包括时间序列分析、网络分析和深度仔细阅读,深入追踪该地区与新冠疫情相关的虚假信息,比较各国之间是否存在行为模式。我们依靠开放的推特应用程序编程接口连接,从拉丁美洲六个主要事实核查机构的公共账户收集数据,即阿根廷()、巴西()、智利()、哥伦比亚(自 )、墨西哥(自 )和委内瑞拉()。这些账号总共发布了2020年1月至7月期间收集的102379条推文。我们的研究深入了解了国家层面以外的在线信息传播动态,并展示了这一时期政治与健康危机是如何交织在一起的。我们的方法能够在信息过剩的时期对主题进行聚类,因为我们不仅要应对疫情,还要应对信息疫情,找出理解和减缓虚假信息传播的机会。