An intelligent spam detection framework using fusion of spammer behavior and linguistic.
The diverse types of fake text generation practices by spammer make spam detection challenging. Existing works use manually designed discrete textual or behavior features, which cannot capture complex global semantics of text and reviews. Some studies use limited features while neglecting other sign...
Saved in:
Main Authors: | Amna Iqbal, Muhammad Younas, Muhammad Kashif Hanif, Muhammad Murad, Rabia Saleem, Muhammad Aater Javed |
---|---|
Format: | Article |
Language: | English |
Published: |
Public Library of Science (PLoS)
2025-01-01
|
Series: | PLoS ONE |
Online Access: | https://doi.org/10.1371/journal.pone.0313628 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Spam detection using hybrid model on fusion of spammer behavior and linguistics features
by: Amna Iqbal, et al.
Published: (2025-03-01) -
An Intelligent Framework Based on Deep Learning for SMS and e-mail Spam Detection
by: Umair Maqsood, et al.
Published: (2023-01-01) -
Deteksi Spam Berbahasa Indonesia Berbasis Teks Menggunakan Model Bert
by: Muhammad Basil Musyaffa Amin, et al.
Published: (2024-12-01) -
Weibo spammers’ identification algorithm based on Bayesian model
by: Yan-mei ZHANG, et al.
Published: (2017-01-01) -
Feature importance analysis for spammer detection in Sina Weibo
by: Yu-xiang ZHANG, et al.
Published: (2016-08-01)