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Neural Moderation of ASMR Erotica Content in Social Networks

  • Yixin Chen
  • , Di Jiang
  • , Conghui Tan
  • , Yuanfeng Song
  • , Chen Zhang
  • , Lei Chen

Research output: Journal article publication › Journal article › Academic research › peer-review

Abstract

With the popularity of video/audio streaming applications in recent years, the wide spread of Autonomous Sensory Meridian Response (ASMR) erotica content is becoming a serious issue in social networks. Due to the subtle nature of ASMR erotica and its relative rareness in real scenario, detecting ASMR erotica contents is a challenging task. In this article, we propose a novel neural framework for ASMR erotica content moderation. The proposed framework consists of a pipeline of novel strategies to tackle challenges unique in ASMR Erotica Contents such as data scarcity and imbalanced data. Based on large-scale industrial data, the proposed framework demonstrates high moderation accuracy in quantitative analysis and significantly outperforming the existing counterparts.

Original languageEnglish
Pages (from-to)275-280
Number of pages6
JournalIEEE Transactions on Knowledge and Data Engineering
Volume36
Issue number1
DOIs
Publication statusPublished - 1 Jan 2024

Keywords

  • ASMR
  • content moderation
  • neural network

ASJC Scopus subject areas

  • Information Systems
  • Computer Science Applications
  • Computational Theory and Mathematics

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