INTERNATIONAL JOURNAL OF SCIENTIFIC DEVELOPMENT AND RESEARCH International Peer Reviewed & Refereed Journals, Open Access Journal ISSN Approved Journal No: 2455-2631 | Impact factor: 8.15 | ESTD Year: 2016
open access , Peer-reviewed, and Refereed Journals, Impact factor 8.15
In the modern world where digitization is everywhere, messages in social media has become one of the most vital forms of communication,unlike other chatting-based messaging systems like Facebook, WhatsApp etc.As we all know that Hackers/Spammer tries to intrude in Mobile Computing Device, and send SMS support for mobile devices had become vulnerable, as attacker tries to intrude to the system by sending unwanted messages in the form of links, clicking those link the attacker can gain remote access over the mobile computing device.So,to identify those messages Authors have developed a system which will identify such malicious messages and will identify whether the message is SPAM or HAM(malicious or not malicious).Authors have created a dictionary using the TF-IDF Vectorizer,Naive bayes algorithms ,which will include all the features of words a SPAM SMS possess, based on content of message and referring to this dictionary the system will be classifying the SMS as spam or ham.
Keywords:
Mobile computing device, SMSsupport , Spam detection
Cite Article:
"Social media spam detection using Machine learning", International Journal of Science & Engineering Development Research (www.ijsdr.org), ISSN:2455-2631, Vol.8, Issue 4, page no.703 - 706, April-2023, Available :http://www.ijsdr.org/papers/IJSDR2304123.pdf
Downloads:
000336256
Publication Details:
Published Paper ID: IJSDR2304123
Registration ID:205020
Published In: Volume 8 Issue 4, April-2023
DOI (Digital Object Identifier):
Page No: 703 - 706
Publisher: IJSDR | www.ijsdr.org
ISSN Number: 2455-2631
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