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The mass, fake news, and cognition security

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Abstract

The widespread fake news in social networks is posing threats to social stability, economic development, and political democracy, etc. Numerous studies have explored the effective detection approaches of online fake news, while few works study the intrinsic propagation and cognition mechanisms of fake news. Since the development of cognitive science paves a promising way for the prevention of fake news, we present a new research area called Cognition Security (CogSec), which studies the potential impacts of fake news on human cognition, ranging from misperception, untrusted knowledge acquisition, targeted opinion/attitude formation, to biased decision making, and investigates the effective ways for fake news debunking. CogSec is a multidisciplinary research field that leverages the knowledge from social science, psychology, cognition science, neuroscience, AI and computer science. We first propose related definitions to characterize CogSec and review the literature history. We further investigate the key research challenges and techniques of CogSec, including humancontent cognition mechanism, social influence and opinion diffusion, fake news detection, and malicious bot detection. Finally, we summarize the open issues and future research directions, such as the cognition mechanism of fake news, influence maximization of fact-checking information, early detection of fake news, fast refutation of fake news, and so on.

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Acknowledgements

This work was partially supported by the National Key R&D Program of China (2019QY0600), the National Natural Science Foundation of China (Grant Nos. 61772428, 61725205, 61902320, 61925203, U1636210), and Beijing Advanced Innovation Center for Big Data and Brain Computing.

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Correspondence to Bin Guo.

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Bin Guo, PhD, professor, PhD supervisor of Northwestern Polytechnical University, China. He is a senior member of CCF. His main research interests include: ubiquitous computing, social and community intelligence, urban big data mining, mobile crowd sensing and human-computer interaction.

Yasan Ding is a PhD candidate at Northwestern Polytechnical University, China. His main research interest is social media data mining.

Yueheng Sun, PhD, associate professor of Tianjin University, China. His main research interests include: social network analysis, social media data processing and their applications in social management.

Shuai Ma, PhD, professor, PhD supervisor of Beihang University, China. He is a senior member of CCF. His main research interests include: big data, database theory and systems, graph and social data analysis, data cleaning and data quality.

Ke Li is a PhD candidate at Northwestern Polytechnical University, China. His main research interests include: probabilistic graphical model and social media mining.

Zhiwen Yu, PhD, professor, PhD supervisor of Northwestern Polytechnical University, China. He is a senior member of CCF. His main research interests include: pervasive computing, context aware systems, personalization, recommendation technology, mobile social networks and multimedia intelligent service.

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Guo, B., Ding, Y., Sun, Y. et al. The mass, fake news, and cognition security. Front. Comput. Sci. 15, 153806 (2021). https://doi.org/10.1007/s11704-020-9256-0

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