AN ADAPTIVE SOCIAL SPAMMER DETECTION MODEL WITH SEMI-SUPERVISED BROAD LEARNING

+91-7667918914 iarjset@gmail.com 0 Items International Advanced Research Journal in Science, Engineering and Technology A Monthly Peer-Reviewed Multidisciplinary Journal ISSN Online 2393-8021 ISSN Print 2394-1588 Since 2014 Home About About IARJSET Aims and Scope Editorial Board Editorial Policies Publication Ethics Publication Policies Indexing and Abstracting Citation Index License Information Authors How can I publish my paper? Instructions to Authors Benefits to Authors Why Publish in IARJSET Call for Papers Check my Paper status Publication Fee Details Publication Fee Mode FAQs Author Testimonials Reviewers Topics Peer Review Current Issue & Archives Indexing FAQ’s Contact Select Page AN ADAPTIVE SOCIAL SPAMMER DETECTION MODEL WITH SEMI-SUPERVISED BROAD LEARNING Apoorva.R, Hemanth Kumar B.N Abstract-This approach is highly effective in creating predictions, especially when compared to certain traditional forms of supervised learning. When using ASSD, identifying individuals within a group becomes simpler and requires less effort. To update the spammer detection model without requiring retraining of the model's users, incremental learning is used as a technique because social scammers often modify their behavior to deceive the spammer detection model. When benchmarked against other controlled and semi-supervised machine learning algorithms, the Social Honeypot Dataset is used to compare ASSD's performance. The study's findings suggest that the proposed model outperforms baseline approaches in terms of memory capacity and accuracy. Additionally, ASSD maintains its high accuracy in identifying spammers by continuously updating its model with newly collected data from social media. Downloads: | DOI: 10.17148/IARJSET.2023.10834 How to Cite: [1] Apoorva.R, Hemanth Kumar B.N, "AN ADAPTIVE SOCIAL SPAMMER DETECTION MODEL WITH SEMI-SUPERVISED BROAD LEARNING," International Advanced Research Journal in Science, Engineering and Technology (IARJSET), DOI: 10.17148/IARJSET.2023.10834 Copy Citation Call for Papers Rapid Publication 24/7 April 2026 Submission: eMail paper now Notification: Immediate Publication: Immediately with eCertificates Frequency: Monthly Downloads Paper Format Copyright Form   Submit to iarjset@gmail.com or editor@iarjset.com   Submit My Paper Author CenterHow can I publish my paper? Publication Fee Why Publish in IARJSET Benefits to Authors Guidelines to Authors FAQs (Frequently Asked Questions) Author Testimonials IARJSET ManagementAims and Scope Call for Papers Editorial Board DOI and Crossref Publication Ethics Editorial Policies Publication Policies Subscription / Librarian Conference Special Issue Info ArchivesCurrent Issue & Archives Conference Special Issue Copyright © 2026 IARJSET This work is licensed under a Creative Commons Attribution 4.0 International License. Open chat