Efficiency of Community-Based Content Moderation Mechanisms: A Discussion Focused on Birdwatch

IF 3.6 4区 管理学 Q2 MANAGEMENT
Chenlong Wang, Pablo Lucas
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Abstract

As user-generated online content has been flourishing with both useful information and misinformation. One of the complexities surrounding such phenomena is its huge amounts of data and its associated difficulties to effectively moderate content, particularly as most initiatives are centralised and fraught with its intrinsic trust issues. One of the few examples using mainly a decentralised (i.e., community-driven) mechanism is Twitter’s Community Notes (once named as Birdwatch) experimental project. This paper thus is about testing the efficiency of such community-based content moderation mechanism and scenarios of interest aiming to better understanding how the users themselves better moderate online content. This is done through an agent-based approach and three conclusions are discussed in detail: (1) to some extent the community is able to fight against misinformation, (2) a Birdwatch-like mechanism can indeed boost the community’s content moderation ability, but there is a nontrivial trade-off between social influence and content timeliness and (3) a simple proposition, in the form of a reminder mechanism to users, cannot fulfil the task of improving the content moderation efficiency, which means a different approach to design is needed.

Abstract Image

基于社区的内容管理机制的效率:以《鸟类观察》为重点的讨论
用户生成的在线内容一直在蓬勃发展,其中既有有用的信息,也有错误的信息。围绕这种现象的一个复杂问题是其海量数据以及与之相关的有效管理内容的困难,特别是大多数倡议都是集中式的,充满了内在的信任问题。Twitter 的 "社区笔记"(曾用名 "鸟类观察")实验项目是少数几个主要采用去中心化(即社区驱动)机制的例子之一。因此,本文将测试这种基于社区的内容管理机制的效率和相关场景,旨在更好地了解用户本身如何更好地管理在线内容。本文通过基于代理的方法进行测试,并详细讨论了三个结论:(1) 在一定程度上,社区能够抵制错误信息;(2) 类似 "小鸟观察 "的机制确实能够提高社区的内容节制能力,但在社会影响力和内容及时性之间存在不小的权衡;(3) 以提醒用户机制为形式的简单命题无法完成提高内容节制效率的任务,这意味着需要采用不同的设计方法。
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来源期刊
CiteScore
5.70
自引率
6.70%
发文量
32
期刊介绍: The idea underlying the journal, Group Decision and Negotiation, emerges from evolving, unifying approaches to group decision and negotiation processes. These processes are complex and self-organizing involving multiplayer, multicriteria, ill-structured, evolving, dynamic problems. Approaches include (1) computer group decision and negotiation support systems (GDNSS), (2) artificial intelligence and management science, (3) applied game theory, experiment and social choice, and (4) cognitive/behavioral sciences in group decision and negotiation. A number of research studies combine two or more of these fields. The journal provides a publication vehicle for theoretical and empirical research, and real-world applications and case studies. In defining the domain of group decision and negotiation, the term `group'' is interpreted to comprise all multiplayer contexts. Thus, organizational decision support systems providing organization-wide support are included. Group decision and negotiation refers to the whole process or flow of activities relevant to group decision and negotiation, not only to the final choice itself, e.g. scanning, communication and information sharing, problem definition (representation) and evolution, alternative generation and social-emotional interaction. Descriptive, normative and design viewpoints are of interest. Thus, Group Decision and Negotiation deals broadly with relation and coordination in group processes. Areas of application include intraorganizational coordination (as in operations management and integrated design, production, finance, marketing and distribution, e.g. as in new products and global coordination), computer supported collaborative work, labor-management negotiations, interorganizational negotiations, (business, government and nonprofits -- e.g. joint ventures), international (intercultural) negotiations, environmental negotiations, etc. The journal also covers developments of software f or group decision and negotiation.
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