Combatting Online Extremism: Algorithmic Amplification of Counter-Speech.

打击网络极端主义：反言论的算法放大。

• 批准号: 2876828
• 金额: --
• 依托单位: Swansea University
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2023
• 资助国家: 英国
• 起止时间: 2023 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-2876828
• 关键词: Combatting; Online; Extremism; Algorithmic; Amplification

Terrorists and violent extremists have historically used social media to share terrorist and violent extremist content (TVEC), which can be algorithmically amplified in certain contexts (Alvari et al., 2019). Therefore, it is suggested that algorithms should be utilised to amplifycounter-speech to target audiences, as a countering violent extremism (CVE) strategy (Schmitt et al., 2018). This PhD will explore the effectiveness and ethics surrounding the algorithmic amplification of counter-speech. By exploring the research questions, this research aims to gain a better understanding of the effectiveness of counter-speech at dissuading individuals from extreme narratives, identify counter-speech measurement, monitoring and evaluation (MME) challenges, and determine the effectiveness and limitations of algorithms in amplifying counter-speech to targetaudiences. Additionally, this research will identify the key ethical principles that should underpin the algorithmic amplification of counter-speech, and determine what ethical principles currently underpin campaigns. This research is important to inform policymakers, practitioners, and tech companies of how to ethically and effectively use algorithms to amplify counter-speech, to dissuade individuals from extreme narratives. This is particularly timely given recent regulatory efforts as evidenced by the Online Safety Bill. Furthermore, this research will identify where resourcesand research can address existing challenges. This will aid in combatting online extremism, and mitigate against potential negative impacts associated with counter-speech including; reinforcing extremist views, and increased polarisation.

恐怖分子和暴力极端分子历史上使用社交媒体分享恐怖主义和暴力极端主义内容（TVEC），这些内容在某些情况下可以通过算法放大（Alvari等人，2019年）。因此，建议应利用算法将反言论放大到目标受众，作为对抗暴力极端主义（CVE）的策略（施密特等人，2018年）。这个博士将探讨反言论的算法放大的有效性和道德。通过探索研究问题，本研究旨在更好地了解反言论在劝阻个人极端叙事方面的有效性，确定反言论测量，监测和评估（MME）的挑战，并确定算法在放大反言论的有效性和局限性。此外，这项研究将确定应该支持反言论的算法放大的关键道德原则，并确定目前支持运动的道德原则。这项研究对于告知政策制定者、从业者和科技公司如何在道德上和有效地使用算法来放大反言论，劝阻个人不要采取极端言论非常重要。考虑到最近的监管努力，这是特别及时的，正如《在线安全法案》所证明的。此外，这项研究将确定资源和研究可以解决现有的挑战。这将有助于打击网络极端主义，并减轻与反言论相关的潜在负面影响，包括强化极端主义观点和加剧两极分化。