Understanding and Improving User-controlled Content Moderation Systems on Social Media

Abstract

This thesis presents a comprehensive exploration of the design and execution of user-controlled content moderation systems that prioritize both fairness and efficiency. These systems range from decentralised blocklists on Twitter to Web3 content moderation (referred to as ''mute'') on memo.cash. memo.cash is a microblogging platform built on the Bitcoin Cash (BCH) blockchain and stands out as the only Web3 platform that enables user-to-user moderation. In contrast, other Web3 platforms like Steemit and Noise.cash employ a less decentralized approach, involving community moderators and administrators. Through extensive data mining, encompassing social interactions and moderation actions from 2.8 million Twitter users and 24 thousand memo.cash users, a thorough analysis of user behaviour among moderated users and moderators, and in-depth machine learning classification and moderation recommendation, this research offers insights into the perspectives and practices of various stakeholders. These stakeholders include users who invest time or financial resources in moderation and individuals whose timelines are affected by content hiding. This study not only furnishes theoretical insights but also offers practical guidance. It prompts the challenges of individual users engaging in moderation while upholding the principles of free speech. It also delves into designing solutions that cater to the diverse needs of user groups and the integration of automated moderation tools