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Exploring content moderation in the decentralised web

the pleroma case
Authors: Anaobi Ishaku Hassan; Aravindh Raman; Ignacio Castro; Haris Bin Zia; Emiliano De Cristofaro; Nishanth Sastry; Gareth Tyson;

Exploring content moderation in the decentralised web

Abstract

Decentralising the Web is a desirable but challenging goal. One particular challenge is achieving decentralised content moderation in the face of various adversaries (e.g. trolls). To overcome this challenge, many Decentralised Web (DW) im- plementations rely on federation policies. Administrators use these policies to create rules that ban or modify content that matches specific rules. This, however, can have unintended consequences for many users. In this paper, we present the first study of federation policies on the DW, their in-the-wild usage, and their impact on users. We identify how these poli- cies may negatively impact ���innocent��� users and outline pos- sible solutions to avoid this problem in the future.

Keywords

FOS: Computer and information sciences, Computer Science - Computers and Society, Computers and Society (cs.CY)

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
views
OpenAIRE UsageCountsViews provided by UsageCounts
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17
Top 10%
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7
11
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