言论自由还是传播自由?减少社交网络恶意内容的策略

IF 6.7 1区 计算机科学 Q1 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE Decision Support Systems Pub Date : 2024-04-27 DOI:10.1016/j.dss.2024.114235
Saurav Chakraborty , Sandeep Goyal , Annamina Rieder , Agnieszka Onuchowska , Donald J. Berndt
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引用次数: 0

摘要

恶意内容威胁着社交网络内容的完整性和质量。研究和实践都尝试过网络干预策略来遏制恶意内容的传播。这些策略缺乏效率,针对的是恶意内容传播者,并且限制了言论自由。我们借鉴了偏好依附文献和认知负荷理论,利用网络形成机制、信息共享和人类有限的认知能力,提出了另一种内容管理策略--偏好抑制内容管理(Preferentiality Dampened Feed Management)。我们使用一个基于代理的模型,利用 Twitter 的经验数据和先前文献的研究成果,将该策略与其他既定策略进行了比较和对比。两个实验的结果表明,我们提出的策略在遏制恶意内容传播方面比其他已有策略更有效。我们的工作对网络干预文献具有重要意义,对平台提供商、社交媒体用户和社会也有实际影响。
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Freedom of speech or freedom of reach? Strategies for mitigating malicious content in social networks

Malicious content threatens the integrity and quality of content in social networks. Research and practice have experimented with network intervention strategies to curb malicious content propagation. These strategies lack efficiency, target malicious content propagators, and abridge freedom of speech. We draw upon the preferential attachment literature and cognitive load theory to employ the mechanisms of network formation, information sharing, and limited human cognitive capacities to propose an alternative feed management strategy—Preferentiality Dampened Feed Management. We compare and contrast this strategy against other established strategies using an agent-based model that utilizes empirical data from Twitter and findings from the prior literature. The results from our two experiments suggest that our proposed strategy is more effective in curbing malicious content propagation than other established strategies. Our work has important implications for the network interventions literature and practical implications for platform providers, social media users, and society.

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来源期刊
Decision Support Systems
Decision Support Systems 工程技术-计算机:人工智能
CiteScore
14.70
自引率
6.70%
发文量
119
审稿时长
13 months
期刊介绍: The common thread of articles published in Decision Support Systems is their relevance to theoretical and technical issues in the support of enhanced decision making. The areas addressed may include foundations, functionality, interfaces, implementation, impacts, and evaluation of decision support systems (DSSs).
期刊最新文献
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