Musawer Hakimi, Baryali Sazish, Mohammad Aziz Rastagari, Kror Shahidzay
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The methodology involved searching academic databases such as PubMed, Scopus, IEEE Xplore, and Google Scholar using predefined search terms and inclusion criteria. The results reveal a diverse range of AI-driven approaches for addressing safety and security concerns on social media platforms, including enhanced threat detection, automated content moderation, and real-time response mechanisms. However, the deployment of AI in social media contexts also raises ethical challenges such as algorithm bias, privacy concerns, and lack of explain ability. The conclusion emphasizes the importance of ongoing research, collaboration, and ethical guidelines to maximize the benefits of AI while minimizing its potential risks. 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引用次数: 0
摘要
社交媒体平台的激增给通信和连接带来了革命性的变化,但也带来了与安全和安保有关的新挑战。为此,研究人员和从业人员转而利用人工智能(AI)来开发降低网络风险的创新解决方案。本系统性文献综述探讨了人工智能在促进社交媒体安全和安保方面的主要应用、方法、益处、局限性、伦理考虑和未来方向。综述综合了计算机科学、工程学和社会科学等不同学科的各种学术文章的研究成果。研究方法包括使用预定义的搜索条件和收录标准搜索 PubMed、Scopus、IEEE Xplore 和 Google Scholar 等学术数据库。研究结果表明,有多种人工智能驱动的方法可用于解决社交媒体平台上的安全和安保问题,包括增强威胁检测、自动内容审核和实时响应机制。然而,在社交媒体环境中部署人工智能也会带来道德挑战,如算法偏差、隐私问题和缺乏解释能力。结论强调了持续研究、合作和伦理准则的重要性,以最大限度地发挥人工智能的优势,同时最大限度地降低其潜在风险。这篇综述深入分析了人工智能和社交媒体这一快速发展领域的当前趋势、挑战和未来方向,为日益增多的人工智能和社交媒体文献做出了贡献。
Artificial Intelligence for Social Media Safety and Security: A Systematic Literature Review
The proliferation of social media platforms has revolutionized communication and connectivity, but it has also introduced new challenges related to safety and security. In response, researchers and practitioners have turned to artificial intelligence (AI) to develop innovative solutions for mitigating online risks. This systematic literature review explores the key applications, methodologies, benefits, limitations, ethical considerations, and future directions of AI in promoting social media safety and security. The review synthesizes findings from various scholarly articles spanning various disciplines, including computer science, engineering, and social sciences. The methodology involved searching academic databases such as PubMed, Scopus, IEEE Xplore, and Google Scholar using predefined search terms and inclusion criteria. The results reveal a diverse range of AI-driven approaches for addressing safety and security concerns on social media platforms, including enhanced threat detection, automated content moderation, and real-time response mechanisms. However, the deployment of AI in social media contexts also raises ethical challenges such as algorithm bias, privacy concerns, and lack of explain ability. The conclusion emphasizes the importance of ongoing research, collaboration, and ethical guidelines to maximize the benefits of AI while minimizing its potential risks. This review contributes to the growing body of literature on AI and social media by providing insights into current trends, challenges, and future directions in this rapidly evolving field.