Classification of online information evaluation processes and methodologies for teaching in the fake news detection
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Abstract
Current online information flows have taken on immeasurable dimensions, thereby influencing the masses, both positively and negatively, thus allowing decision-making and the generation of ways of thinking, which on many occasions turn out to be unfounded and cause misinformation. The analysis is based on the need to generate an epistemic contribution around online information processes for the purposes of classification and general characterization with a special focus on emerging countries (especially Latin American) through documentary research. This proposal identifies the construction of a taxonomy of information evaluation processes, consisting of three general groups: (1) structured ones (coming from formal education and through systematic content that causes explicit learning); (2) unstructured ones (deliberately acquired, through non-formal processes, which generate tacit learning that is not necessarily correct or well-founded); and (3) complementary ones (referring to alternative methodologies for diagnosing misinformation situations). The paper concludes by presenting proposals for various forms of intervention and identifying best practices in order to avoid biases in misinterpretation, especially when the information is false.
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