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Automatic Moderation of User-Generated Content
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Author(s): Issa Annamoradnejad (Sharif University of Technology, Iran)and Jafar Habibi (Sharif University of Technology, Iran)
Copyright: 2023
Pages: 12
Source title:
Encyclopedia of Data Science and Machine Learning
Source Author(s)/Editor(s): John Wang (Montclair State University, USA)
DOI: 10.4018/978-1-7998-9220-5.ch079
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Abstract
In recent years, most popular websites, such as Facebook and Wikipedia, depend on user involvement and content generation for their popularity and growth. Due to the vast expanse of these systems in terms of users and posts, manual verification of new content by the administrators or official moderators is not feasible, and these systems require scalable solutions. In this research, the authors show the emerging need for automated moderation of user-generated content using the latest machine learning and data science methods. This article will present novel ideas to create a real-world recommendation system that can assist system users and moderators in identifying the existing issues of old questions, sharing new high-quality questions, reducing the time needed for performing moderation actions, and improving the overall quality of the system.
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