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
-
Mining Potential Spammers from Mobile Call Logs
by: Zhipeng Liu, et al.
Published: (2015-04-01) -
Feature importance analysis for spammer detection in Sina Weibo
by: Yu-xiang ZHANG, et al.
Published: (2016-08-01) -
StopSpamX: A multi modal fusion approach for spam detection in social networking
by: Dasari Siva Krishna, et al.
Published: (2025-06-01) -
Spammer group detection based on cascading and clustering of core figures
by: Qianqian Jiang, et al.
Published: (2025-07-01) -
An Improved Framework for Content- and Link-Based Web-Spam Detection: A Combined Approach
by: Asim Shahzad, et al.
Published: (2021-01-01)