Social media content moderation

Ahmed Abdalsamad Mohamed Amin Wafi

Master's thesis

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.

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

Keywords

Content Moderation, Media Censorship, Algorithmic Moderation

Language used: English

Date on which the thesis was submitted / produced: 4. 12. 2023

Thesis defence

• Date of defence: 29. 1. 2024
• Supervisor: Antonín Pavlíček
• Reader: Jana Syrovátková

Vysoká škola ekonomická v Praze

Master programme:
Information Systems Management