论文标题
帮助用户在社交媒体上解决算法威胁：多媒体研究议程
Helping Users Tackle Algorithmic Threats on Social Media: A Multimedia Research Agenda
论文作者
论文摘要
参与社交媒体平台有很多好处，但也带来了重大威胁。用户通常会面临意外的隐私丧失，被错误/虚假信息轰炸，或者由于内容过多而被困在过滤器气泡中。由于隐藏的AI驱动算法在幕后工作以塑造用户的思想，态度和行为，因此进一步加剧了这些威胁。我们研究了多媒体研究人员如何帮助解决这些问题，从而为社交媒体用户提供竞争环境。我们对社交媒体上的算法威胁进行了全面的调查，并将其用作镜头，以制定具有效但重要的研究议程，以实现有效和实时用户。我们进一步实施概念性原型，并与专家一起评估它，以补充我们的研究议程。本文呼吁通过使用机器学习和多媒体内容分析技术，但以透明的方式和为用户的利益来应对社交媒体上算法威胁的解决方案。
Participation on social media platforms has many benefits but also poses substantial threats. Users often face an unintended loss of privacy, are bombarded with mis-/disinformation, or are trapped in filter bubbles due to over-personalized content. These threats are further exacerbated by the rise of hidden AI-driven algorithms working behind the scenes to shape users' thoughts, attitudes, and behavior. We investigate how multimedia researchers can help tackle these problems to level the playing field for social media users. We perform a comprehensive survey of algorithmic threats on social media and use it as a lens to set a challenging but important research agenda for effective and real-time user nudging. We further implement a conceptual prototype and evaluate it with experts to supplement our research agenda. This paper calls for solutions that combat the algorithmic threats on social media by utilizing machine learning and multimedia content analysis techniques but in a transparent manner and for the benefit of the users.
