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
  • [21] Enhancing Detection of Arabic Social Spam Using Data Augmentation and Machine Learning
    Alkadri, Abdullah M.
    Elkorany, Abeer
    Ahmed, Cherry
    [J]. APPLIED SCIENCES-BASEL, 2022, 12 (22):
  • [22] An Exploration of Machine Learning and Deep Learning Techniques for Offensive Text Detection in Social Media-A Systematic Review
    Sharma, Geetanjali
    Brar, Gursimran Singh
    Singh, Pahuldeep
    Gupta, Nitish
    Kalra, Nidhi
    Parashar, Anshu
    [J]. INTERNATIONAL CONFERENCE ON INNOVATIVE COMPUTING AND COMMUNICATIONS, ICICC 2022, VOL 3, 2023, 492 : 541 - 559
  • [23] Enhancing the government accounting information systems using social media information: An application of text mining and machine learning
    Duan, Huijue Kelly
    Vasarhelyi, Miklos A.
    Codesso, Mauricio
    Alzamil, Zamil
    [J]. INTERNATIONAL JOURNAL OF ACCOUNTING INFORMATION SYSTEMS, 2023, 48
  • [24] Harnessing the Power of Text Mining for the Detection of Abusive Content in Social Media
    Chen, Hao
    Mckeever, Susan
    Delany, Sarah Jane
    [J]. ADVANCES IN COMPUTATIONAL INTELLIGENCE SYSTEMS, 2017, 513 : 187 - 205
  • [25] Machine Learning for the Detection of Spam in Twitter Networks
    Wang, Alex Hai
    [J]. E-BUSINESS AND TELECOMMUNICATIONS, 2012, 222 : 319 - 333
  • [26] Comparison of machine learning techniques for spam detection
    Ghosh, Argha
    Senthilrajan, A.
    [J]. MULTIMEDIA TOOLS AND APPLICATIONS, 2023, 82 (19) : 29227 - 29254
  • [27] A Study of Machine Learning Classifiers for Spam Detection
    Trivedi, Shrawan Kumar
    [J]. 2016 4TH INTERNATIONAL SYMPOSIUM ON COMPUTATIONAL AND BUSINESS INTELLIGENCE (ISCBI), 2016, : 176 - 180
  • [28] Comparison of machine learning techniques for spam detection
    Argha Ghosh
    A. Senthilrajan
    [J]. Multimedia Tools and Applications, 2023, 82 : 29227 - 29254
  • [29] Comparison of Machine Learning Algorithms for Spam Detection
    Sadia, Azeema
    Bashir, Fatima
    Khan, Reema Qaiser
    Bashir, Amna
    Khalid, Ammarah
    [J]. JOURNAL OF ADVANCES IN INFORMATION TECHNOLOGY, 2023, 14 (02) : 178 - 184
  • [30] Review Spam Detection using Machine Learning
    Radovanovic, Drasko
    Krstajic, Boza
    [J]. 2018 23RD INTERNATIONAL SCIENTIFIC-PROFESSIONAL CONFERENCE ON INFORMATION TECHNOLOGY (IT), 2018,