Scams are fraudulent activities aiming to deceive individuals into relinquishing money, property, or rights, and they have proliferated in the context of widespread misinformation and disinformation. In this paper, we propose strategies and a research plan to address key questions about the exploitation of new communication technologies by scammers, the prevalence and nature of different scam types, and the language characteristics and appeals used in scamming content. We aim to develop a comprehensive taxonomy of scams and identify factors that contribute to their persuasiveness. Additionally, we propose the use of advanced technologies, including artificial intelligence, physiological measures, and brain mapping, to detect, investigate, and combat scams. The findings will inform the creation of educational resources and interventions, including databases, short videos, an online repository for crowdsourcing scam cases, community training programs, and online courses aimed at improving scam detection and prevention. By leveraging interdisciplinary expertise, this study seeks to develop a multi-faceted approach to mitigate the impact of scams and foster a more informed and resilient public.

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Understanding and Fighting Scams: Media, Language, Appeals and Effects

  • Shuhua Zhou,
  • Xiao Fan Liu,
  • Fiona Fui-Hoon Nah,
  • Simon Harrison,
  • Xinzhi Zhang,
  • Shanshan Zhen,
  • Dannii Yeung,
  • Janet Hui-wen Hsiao,
  • Ray LC,
  • Antoni B. Chan,
  • Xiaohui Wang,
  • Crystal Li Jiang,
  • Fen Lin,
  • Jixing Li,
  • Andus Wing-Kuen Wong,
  • Leanne Lai-Hang Chan,
  • Bert George,
  • Ping Li

摘要

Scams are fraudulent activities aiming to deceive individuals into relinquishing money, property, or rights, and they have proliferated in the context of widespread misinformation and disinformation. In this paper, we propose strategies and a research plan to address key questions about the exploitation of new communication technologies by scammers, the prevalence and nature of different scam types, and the language characteristics and appeals used in scamming content. We aim to develop a comprehensive taxonomy of scams and identify factors that contribute to their persuasiveness. Additionally, we propose the use of advanced technologies, including artificial intelligence, physiological measures, and brain mapping, to detect, investigate, and combat scams. The findings will inform the creation of educational resources and interventions, including databases, short videos, an online repository for crowdsourcing scam cases, community training programs, and online courses aimed at improving scam detection and prevention. By leveraging interdisciplinary expertise, this study seeks to develop a multi-faceted approach to mitigate the impact of scams and foster a more informed and resilient public.