No abstract

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 (Chequeado), Brazil (Agência Lupa), Chile (Mala Espina Check), Colombia (Colombia Check from Consejo de Redacciín), Mexico (El Sabueso from Animal Polótico) and Venezuela (Efecto Cocuyo). 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.

Innovation in journalism became an important element to determine the current and future direction of the profession. Through incremental and cumulative transformations over time, because of many obstacles faced inside the newsrooms, journalism has suffered from significant and fundamental changes, including the deployment of data journalism. In Latin America, the practice has seen an increasing expansion in the last years. Nevertheless, there are important technological gaps that limit its development. The present study draws upon literature on data journalism, media management, and sociology, aiming to contribute theoretically to data journalism research. Our findings show that beyond the technological approach, practitioners are relying on data evangelists, collaboration, and audience-centered innovation to produce data storytelling in their newsrooms. On the other hand, these alliances form "homophily" and "endogamy" features that limit the dissemination of the practice, which must consider the potential implications for the social distance of the audiences. It argues that Latin American professionals are distancing themselves from technological determinism to embrace a more audience-centric innovation in newsrooms. Finally, it also states that it is important to take into account those limitations, as they pose obstacles for data journalism innovation research knowledge. The article concludes with an agenda for future research.

In Brazil, inequalities are visually represented in its favelas. These neighborhoods are usually comprised of low-income informal settlements neglected by governments and often forgotten by mainstream media. The pervasive nature of information and communications technology (ICT) has brought new ways to produce news content in the media industry, giving voice to these communities. Thus, small, alternative, community, or nonmainstream media became a vital terrain of opposition activism. Drawing on user participation, collaboration, and data journalism theories, this article analyzes three alternative media organizations (Agência Mural, data_labe, and Favela em Pauta), which proposed producing data-driven content by, for, and about favelas through a mixed-method research design. Results show that four contributing factors tend to help these organizations to produce data stories despite these challenges: citizen participation, activism, collaboration, and humanizing data. The article concludes by demonstrating how elements developed in these initiatives and presents an agenda for future research.

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 amongst 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 (API) connection to gather data from public accounts of the six major fact-checking agencies in Latin America, namely: Argentina ( Chequeado ), Brazil ( Agência Lupa ), Chile ( Mala Espina Check ), Colombia ( Colombia Check from Consejo de Redacción ), Mexico ( El Sabueso from Animal Político ) and Venezuela ( Efecto Cocuyo ). 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.