Titlebook: Artificial Misinformation; Exploring Human-Algo Donghee Shin Book 2024 The Editor(s) (if applicable) and The Author(s), under exclusive lic

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Misinformation and Algorithmic Biasom unintended privacy infringements to solidifying societal biases of gender, race, ethnicity, and culture. The significance of the data used in training algorithms should not be underestimated. Humans should play a part in the datafication of algorithms, as preventing the spread of misinformation i

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Misinformation, Extremism, and Conspiracies: Amplification and Polarization by Algorithmsthe pathways by which users access far-right content are manifold and that a large part of this can be ascribed to platform recommendations through a positive feedback loop. The results are consistent with the proposition that the generation and adoption of extreme content on TikTok largely reflect

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Misinformation Processing Model: How Users Process Misinformation When Using Recommender Algorithmsn and whether explainability further moderates this relationship. The findings showed that users with a high heuristic processing of normative values and positive diagnostic perception were more likely to proactively discern misinformation. Users with a high cognitive ability to understand informati

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Misinformation and Diversity: Nudging Away from Misinformation Nudging Toward Diversityusers make sense of algorithmic nudges and how nudges influence users’ views on personalization and attitudes toward news diversity. The findings show that algorithmic nudges play a key role in understanding normative values in NRS, which then influence the user’s intention to consume diverse news.

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Misinformation, Paradox, and Nudge: Combating Misinformation Through Nudgingof nudging in decreasing the chances of consuming and spreading misinformation. The key is how to ensure that algorithmic nudges are used in an effective way and whether the nudge could also help to achieve a sustainable way of life. This chapter discusses the principles and dimensions of the nudgin

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Misinformation and Generative AI: How Users Construe Their Sense of Diagnostic Misinformationhigh heuristic processing of ethical values and positive diagnostic perception were more likely to proactively discern misinformation than users with low heuristic processing and low diagnostic perception. When exposed to misinformation from GenAI, users’ construed diagnosticity of misinformation ca