A systematic literature review on disinformation: Toward a unified taxonomical framework

Abstract

The scale, volume, and distribution speed of disinformation raise concerns in governments, businesses, and citizens. To respond effectively to this problem, we first need to disambiguate, understand, and clearly define the phenomenon. Our online information landscape is characterized by a variety of different types of false information. There is no commonly agreed typology framework, specific categorization criteria, and explicit definitions as a basis to assist the further investigation of the area. Our work is focused on filling this need. Our contribution is twofold. First, we collect the various implicit and explicit disinformation typologies proposed by scholars. We consolidate the findings following certain design principles to articulate an all-inclusive disinformation typology. Second, we propose three independent dimensions with controlled values per dimension as categorization criteria for all types of disinformation. The taxonomy can promote and support further multidisciplinary research to analyze the special characteristics of the identified disinformation types.

Una nueva taxonomía del uso de la imagen en la conformación interesada del relato digital. Deep fakes e inteligencia artificial

“…Molina et al (2019) categorizan siete tipos de contenido falso -desde las noticias falsas hasta el periodismo ciudadano-encuadrados en cuatro dominios: mensaje, fuente, estructura y red. Una aproximación similar siguen Kapantai et al (2020), también centrada en tipos y dominios. Por su parte Valchanov (2018) resulta original en su tipología al incluir en la clasificación la incompetencia o la falta de exhaustividad de los periodistas.…”

Learning from Each Other—A Bibliometric Review of Research on Information Disorders

“…More recently, Kapantai et al, conducted a systematic literature review on disinformation with a clear objective "to identify and define the various underlying content types in the information disorder ecosystem and organize them" [11] (p. 17). They proposed a unified typology framework for disinformation to be validated in the years to come.…”

“…Regarding the collaborative research aspects, our study's results can be summed up as follows: There were some collaboration patterns between the highly cited, most productive authors, countries tended to work together for a core-country, and regional cooperation among institutions predominated. Most of all, we need to create collaboration mechanisms that involve not only higher education institutions and research units, but also monitoring organizations, experts in the field, social media platforms, government and decision makers [11] to make sure that data deficits can be identified early on and replaced with accessible, evidence-based information [83]. These results are in line with those of Skarzauskiene et al [126], who argue that in this way the successful spread of harmful narratives can be prevented.…”

“…Researching information disorders is a challenging task and any study has limitations. If Hansson et al [15] identify six types of harmful information during the pandemic in Europe, Kapantai et al [11] (p. 1) reported that, although there is rich scientific literature on diverse topics, it does not address ID in a unitary way. It only deals separately with its elements, with "no commonly agreed typology framework, specific categorization criteria".…”

Stiffness Analysis to Predict the Spread Out of Fake Information

“…In fact, nowadays, the majority of the population considers the Internet and social media as the main channels of transmitting news. However, at the same time, social media are also believed to be the main sources of transmission of disinformation and fake news [1][2][3][4][5][6][7][8][9][10][11][12][13][14][15][16][17][18].…”