|
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 |
Imp Links for Author
Imp Links for Reviewer
Research Area
Subscribe IJSDR
Visitor Counter
Copyright Infringement Claims
Indexing Partner
|
Published Paper Details
|
|
| Paper Title: | Improving Spam Detection on Online Social Media with hybrid classification techniques on Twitter platform |
| Authors Name: | Rohini More , Sunilkumar N. Jaiswal |
| Unique Id: | IJSDR1806006 |
| Published In: | Volume 3 Issue 6, June-2018 |
| Abstract: | As the World Wide web is increasing day by day, tweets ar a reliable thanks to communicate and conjointly the fastest thanks to send information from one place to a special. Most transactions, whether or not or not they're a business or a business, use Twitter as a communications mode. Twitter is also a completely effective declare communication as a results of it helps in amount of your time communication, that saves time and cash. in addition to their edges, tweets have jointly been sick with spam attacks. Spam tweets ar typically accustomed send tweets in bulk to the sender. Spam will flood world wide web with many copies of comparable messages scattered at intervals the main points. These messages ar sent to unwanted recipients. we'll analyze information|the info|the information} mining ways for spam information throughout a spread of the thanks to obtain the foremost effective classification for Tweeting. As a region of this text, we'll describe the classification of Tweet to identify spam, not spam. For this reason, we've got an inclination to use the Naive theorem Classifier and build a speaker organization to exclude spam and not spam. |
| Keywords: | Tweets spam, Classification, Feature Extraction, Naive Bayesian Classifier,Stanford Classifier |
| Cite Article: | "Improving Spam Detection on Online Social Media with hybrid classification techniques on Twitter platform", International Journal of Science & Engineering Development Research (www.ijsdr.org), ISSN:2455-2631, Vol.3, Issue 6, page no.26 - 32, June-2018, Available :http://www.ijsdr.org/papers/IJSDR1806006.pdf |
| Downloads: | 000336851 |
| Publication Details: | Published Paper ID: IJSDR1806006 Registration ID:180364 Published In: Volume 3 Issue 6, June-2018 DOI (Digital Object Identifier): Page No: 26 - 32 Publisher: IJSDR | www.ijsdr.org ISSN Number: 2455-2631 |
|
Click Here to Download This Article |
|
| Article Preview | |
|
|
|
Major Indexing from www.ijsdr.org
| Google Scholar | ResearcherID Thomson Reuters | Mendeley : reference manager | Academia.edu |
| arXiv.org : cornell university library | Research Gate | CiteSeerX | DOAJ : Directory of Open Access Journals |
| DRJI | Index Copernicus International | Scribd | DocStoc |
Track Paper
Important Links
Conference Proposal
ISSN
 |
 |
DOI (A digital object identifier)
  Providing A digital object identifier by DOI How to GET DOI and Hard Copy Related |
Open Access License Policy
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License
|
 |
 |
 |
Social Media
Indexing Partner |
|||
| Copyright © 2024 - All Rights Reserved - IJSDR | |||
Facebook Twitter Instagram LinkedIn