Social media content moderation
Thesis title: | Social media content moderation |
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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 |
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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 |
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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 |
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Date of submission: | 4. 12. 2023 |
Date of defense: | 29. 1. 2024 |
Identifier in the InSIS system: | https://insis.vse.cz/zp/79531/podrobnosti |