Online Harassment Detection using Machine Learning

被引:1
|
作者
Ahirwar, Raj [1 ]
Ajay, M. [1 ]
Sathyabalan, N. [1 ]
Lakshmi, K. [1 ]
机构
[1] Periyar Maniammai Inst Sci & Technol PMIST, Thanjavur, Tamil Nadu, India
关键词
SVM; Logistic regression; Random forest; Naive Bayes; Naturallanguage processing; machine learning;
D O I
10.1109/ICICT54344.2022.9850516
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
Online communication has become more accessible with the recent digitalization techniques. This advancement also comes with its own advantages and disadvantages. The major disadvantage is the occurrence of bullying and online harassment in cyberspace, which is referred to as cyberbullying. A lot of effort has been taken to deal with this problem. The sufferers will only know the extent of their psychological and mental consequences. Several research studies have proposed different techniques for identifying cyberbullying, however the majority of them focus on a specific job, such as text recognition systems by using Machine Learning (ML) techniques or voice recognition systems using Natural Language Processing (NLP) techniques. To overcome this drawback, the proposed research study offers a multitasking approach, which can work with both text and audio data.
引用
收藏
页码:1222 / 1224
页数:3
相关论文
共 50 条
  • [21] Online Testing in Machine Learning Approach for Fall Detection
    Martinez-Villasenor, Lourdes
    Ponce, Hiram
    Nunez-Martinez, Jose
    Pacheco, Sofia
    2020 INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS (IJCNN), 2020,
  • [22] Online Anomaly Detection Using Machine Learning and HPC for Power System Synchrophasor Measurements
    Ren, Huiying
    Hou, Zhangshuan
    Etingov, Pavel
    2018 IEEE INTERNATIONAL CONFERENCE ON PROBABILISTIC METHODS APPLIED TO POWER SYSTEMS (PMAPS), 2018,
  • [23] Performance counter based online pipeline bugs detection using machine learning techniques
    Jayaraman, Padma
    Parthasarathi, Ranjani
    MICROPROCESSORS AND MICROSYSTEMS, 2021, 84
  • [24] Online travel mode detection method using automated machine learning and feature engineering
    Soares, Elton F. de S.
    Campos, Carlos Alberto V.
    de Lucena, Sidney C.
    FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE, 2019, 101 : 1201 - 1212
  • [25] Learning to Detect Online Harassment on Twitter with the Transformer
    Bugueno, Margarita
    Mendoza, Marcelo
    MACHINE LEARNING AND KNOWLEDGE DISCOVERY IN DATABASES, ECML PKDD 2019, PT II, 2020, 1168 : 298 - 306
  • [26] An Online Learning Algorithm for Voice Activation Detection Based on a Pretrained Online Extreme Learning Machine
    Zhang, Tianle
    Hou, Muzhou
    Weng, Futian
    Yang, Yunlei
    Sun, Hongli
    Wang, Zheng
    Gao, Zhong
    Luo, Jianshu
    PROCEEDINGS OF THE 2ND INTERNATIONAL CONFERENCE ON COMPUTER SCIENCE AND APPLICATION ENGINEERING (CSAE2018), 2018,
  • [27] Dyscalculia Detection Using Machine Learning
    Subramanyam, Alka
    Jyrwa, Sonakshi
    Bansinghani, Juhi M.
    Dadhakar, Sarthak J.
    Dhingra, Trena, V
    Ramchandani, Umesh R.
    Sengupta, Sharmila
    PATTERN RECOGNITION AND MACHINE INTELLIGENCE, PREMI 2019, PT I, 2019, 11941 : 111 - 120
  • [28] DDoS Detection using Machine Learning
    Nagah, Nour Ahmed
    Bahaa, Mariam
    Elsersy, Wael Farouk
    2024 INTERNATIONAL CONFERENCE ON MACHINE INTELLIGENCE AND SMART INNOVATION, ICMISI 2024, 2024, : 94 - 100
  • [29] Exoplanet detection using machine learning
    Malik, Abhishek
    Moster, Benjamin P.
    Obermeier, Christian
    MONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY, 2022, 513 (04) : 5505 - 5516
  • [30] DETECTION OF MICROPLASTICS USING MACHINE LEARNING
    Chaczko, Zenon
    Wajs-Chaczko, Peter
    Tien, David
    Haidar, Yousef
    PROCEEDINGS OF 2019 INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND CYBERNETICS (ICMLC), 2019, : 258 - 265