Social media content moderation

Thesis title: Social media content moderation
Author: Wafi, Ahmed Abdalsamad Mohamed Amin
Thesis type: Diploma thesis
Supervisor: Pavlíček, Antonín
Opponents: Syrovátková, Jana
Thesis language: English
Abstract:
Utilized by more than fifty percent of people worldwide (number of Internet users 5.3 billion and social media users 4.95 billion) (DataReportal, 2023), there is an unprecedented rise in global dependency of communication on information technology and social media platforms. These platforms functioned originally as entertainment platforms. However, they have evolved to influence public opinions, implement advertising market research, and articulate individual points of view toward social and political matters. This dramatic change has necessitated in-depth academic research into content moderation on user-generated platforms. This study begins by examining the evolution of media censorship and provides a detailed analysis of social media platforms. It critically reviews existing literature to understand the governance models of internet platforms, with a particular focus on the combination of human and algorithmic moderation techniques. The research mainly assesses the effectiveness of Facebook's governance and content moderation, utilizing human judgment and algorithms as an example. The practical aspect of this research evaluates the efficiency of moderation technologies used in enforcing content policies on social media, using Facebook as a case study to analyze the implementation effectiveness of policies through AI-based moderation techniques.
Keywords: Content Moderation; Media Censorship; Algorithmic Moderation
Thesis title: Social Media Content Moderation
Author: Wafi, Ahmed Abdalsamad Mohamed Amin
Thesis type: Diplomová práce
Supervisor: Pavlíček, Antonín
Opponents: Syrovátková, Jana
Thesis language: English
Abstract:
Utilized by more than fifty percent of people worldwide (number of Internet users 5.3 billion and social media users 4.95 billion) (DataReportal, 2023), there is an unprecedented rise in global dependency of communication on information technology and social media platforms. These platforms functioned originally as entertainment platforms. However, they have evolved to influence public opinions, implement advertising market research, and articulate individual points of view toward social and political matters. This dramatic change has necessitated in-depth academic research into content moderation on user-generated platforms. This study begins by examining the evolution of media censorship and provides a detailed analysis of social media platforms. It critically reviews existing literature to understand the governance models of internet platforms, with a particular focus on the combination of human and algorithmic moderation techniques. The research mainly assesses the effectiveness of Facebook's governance and content moderation, utilizing human judgment and algorithms as an example. The practical aspect of this research evaluates the efficiency of moderation technologies used in enforcing content policies on social media, using Facebook as a case study to analyze the implementation effectiveness of policies through AI-based moderation techniques.
Keywords: Media Censorship; Algorithmic Moderation; Content Moderation

Information about study

Study programme: Information Systems Management
Type of study programme: Magisterský studijní program
Assigned degree: Ing.
Institutions assigning academic degree: Vysoká škola ekonomická v Praze
Faculty: Faculty of Informatics and Statistics
Department: Department of Systems Analysis

Information on submission and defense

Date of assignment: 31. 1. 2022
Date of submission: 4. 12. 2023
Date of defense: 29. 1. 2024
Identifier in the InSIS system: https://insis.vse.cz/zp/79531/podrobnosti

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