Advancements in Social Media Content Moderation

The field of social media content moderation is moving towards a more nuanced and multifaceted approach, balancing the need to protect users from harmful content with the importance of preserving freedom of speech. Researchers are exploring innovative methods to optimize this balance, including the use of mechanism design and emotion monitoring. Noteworthy papers include:

  • A study that proposes practical methods to approximate the optimal trade-off between minimizing social distortion and maximizing free speech, providing generalization guarantees for the amount of finite offline data required.
  • A systematic review of antisocial behavior prediction, offering a structured taxonomy of core task types and analyzing trends in modeling techniques.
  • A proposal for a decentralized data arrangement framework to mitigate the impact of social media platforms on user safety, privacy, and security.

Sources

Strategic Filtering for Content Moderation: Free Speech or Free of Distortion?

Before the Outrage: Challenges and Advances in Predicting Online Antisocial Behavior

Emotionally Aware Moderation: The Potential of Emotion Monitoring in Shaping Healthier Social Media Conversations

Mitigation of Social Media Platforms Impact on the Users

Arabic Hate Speech Identification and Masking in Social Media using Deep Learning Models and Pre-trained Models Fine-tuning

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