Spam Detection in Social Media Employing Machine Learning Tool for Text Mining

被引:11
|
作者
Zaman, Zakia [1 ]
Sharmin, Sadia [1 ]
机构
[1] Bangladesh Univ Engn & Technol, Dept Comp Sci & Engn, Dhaka, Bangladesh
关键词
Spam detection; Social Media; Machine Learning; WEKA tool; Text mining;
D O I
10.1109/SITIS.2017.32
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
In recent time, online social networks have been affected by various unwanted threats. Although they provided us with an open platform to share our thoughts with others, however, due to misuse of this powerful resource, general users are in endangered condition. For example, YouTube has been used as a promotional ground by various artist to upload their music videos, movie trailers, etc. and viewers can post their opinion on them. Unfortunately, often malicious users use to post phishing website links, advertisements, and fraudulent information in the comments section, which may transmit viruses or malwares. So, these harmful comments need to be identified in order to continue flawless service of social media. In this study, we have been implemented several classification algorithm to sort out the spam comments on YouTube videos from the legitimate one, their performance measures have been analysed as well as performance of ensemble classifier over single classifier algorithm in the context of text classification has also been highlighted.
引用
收藏
页码:137 / 142
页数:6
相关论文
共 50 条
  • [41] An Analysis of Machine Learning Methods for Spam Host Detection
    Silva, Renato M.
    Yamakami, Akebo
    Almeida, Tiago A.
    [J]. 2012 11TH INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND APPLICATIONS (ICMLA 2012), VOL 2, 2012, : 227 - 232
  • [42] Machine and Deep Learning Algorithms for Twitter Spam Detection
    Alsaffar, Dalia
    Alfahhad, Amjad
    Alqhtani, Bashaier
    Alamri, Lama
    Alansari, Shahad
    Alqahtani, Nada
    Alboaneen, Dabiah A.
    [J]. PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON ADVANCED INTELLIGENT SYSTEMS AND INFORMATICS 2019, 2020, 1058 : 483 - 491
  • [43] Machine Learning-Based Detection of Spam Emails
    Bin Siddique, Zeeshan
    Khan, Mudassar Ali
    Din, Ikram Ud
    Almogren, Ahmad
    Mohiuddin, Irfan
    Nazir, Shah
    [J]. SCIENTIFIC PROGRAMMING, 2021, 2021
  • [44] Email Spam Detection by Machine Learning Approaches: A Review
    Hadi, Mohammad Talib
    Baawi, Salwa Shakir
    [J]. FORTHCOMING NETWORKS AND SUSTAINABILITY IN THE AIOT ERA, VOL 1, FONES-AIOT 2024, 2024, 1035 : 186 - 204
  • [45] Machine Learning Techniques Used for Text Mining
    Godoy Viera, Angel Freddy
    [J]. INVESTIGACION BIBLIOTECOLOGICA, 2017, 31 (71): : 103 - 126
  • [46] Machine learning and text mining of trophic links
    Milani, Ghazal Afroozi
    Bohan, David
    Dunbar, Stuart
    Muggleton, Stephen
    Raybould, Alan
    Tamaddoni-Nezhad, Alireza
    [J]. 2012 11TH INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND APPLICATIONS (ICMLA 2012), VOL 2, 2012, : 410 - 415
  • [47] Spam Short Messages Detection via Mining Social Networks
    Jian-Yun Liu
    Yu-Hang Zhao
    Zhao-Xiang Zhang
    Yun-Hong Wang
    Xue-Mei Yuan
    Lei Hu
    Zhen-Jiang Dong
    [J]. Journal of Computer Science and Technology, 2012, 27 : 506 - 514
  • [48] Spam Short Messages Detection via Mining Social Networks
    刘建芸
    赵宇航
    张兆翔
    王蕴红
    袁雪梅
    胡磊
    董振江
    [J]. Journal of Computer Science & Technology, 2012, (03) : 506 - 514
  • [49] Spam Short Messages Detection via Mining Social Networks
    Liu, Jian-Yun
    Zhao, Yu-Hang
    Zhang, Zhao-Xiang
    Wang, Yun-Hong
    Yuan, Xue-Mei
    Hu, Lei
    Dong, Zhen-Jiang
    [J]. JOURNAL OF COMPUTER SCIENCE AND TECHNOLOGY, 2012, 27 (03) : 506 - 514
  • [50] A Combined Text-Based and Metadata-Based Deep-Learning Framework for the Detection of Spam Accounts on the Social Media Platform Twitter
    Alhassun, Atheer S.
    Rassam, Murad A.
    [J]. PROCESSES, 2022, 10 (03)