[HTML][HTML] Detecting malicious activity in Twitter using deep learning techniques

L Ilias, I Roussaki - Applied Soft Computing, 2021 - Elsevier
Undoubtedly, social media, such as Facebook and Twitter, constitute a major part of our
everyday life due to the incredible possibilities they offer to their users. However, Twitter and …

Coordinated Amplification, Coordinated Inauthentic Behaviour, Orchestrated Campaigns: A Systematic Literature Review of Coordinated Inauthentic Content on …

MF de-Lima-Santos, W Ceron - Map** Lies in the Global Media …, 2024 - taylorfrancis.com
The internet and online social networks have resulted in dramatic changes in the information
landscape. Pessimistic views fear that networks and algorithms can limit exposure to various …

Spade: Multi-stage spam account detection for online social networks

F Concone, GL Re, M Morana… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
In recent years, Online Social Networks (OSNs) have radically changed the way people
communicate. The most widely used platforms, such as Facebook, Youtube, and Instagram …

Advances in spam detection for email spam, web spam, social network spam, and review spam: ML-based and nature-inspired-based techniques

AA Akinyelu - Journal of Computer Security, 2021 - content.iospress.com
Despite the great advances in spam detection, spam remains a major problem that has
affected the global economy enormously. Spam attacks are popularly perpetrated through …

A hybrid framework for bot detection on twitter: Fusing digital DNA with BERT

V Chawla, Y Kapoor - Multimedia Tools and Applications, 2023 - Springer
With the recognition and influence of Twitter on modern society, an enormous amount of
multimedia information is regularly generated and rapidly disseminated on the platform …

A weak-region enhanced Bayesian classification for spam content-based filtering

V Nosrati, M Rahmani, A Jolfaei… - ACM Transactions on …, 2023 - dl.acm.org
This article proposes an improved Bayesian scheme by focusing on the region in which
Bayesian may fail to correctly identify labels and improve classification performance by …

[PDF][PDF] An intelligent ensemble classification method for spam diagnosis in social networks

A Ahraminezhad, M Mojarad… - International Journal of …, 2022 - mecs-press.org
In recent years, the destructive behavior of social networks spammers has seriously
threatened the information security of ordinary users. To reduce this threat, many …

A collaborative abstraction based email spam filtering with fingerprints

P Rajendran, A Tamilarasi, R Mynavathi - Wireless Personal …, 2022 - Springer
Spam detection in emails tends to be an endless research interest among many researchers
and academicians. Even though email communication has become a major role in day to …

A drift aware hierarchical test based approach for combating social spammers in online social networks

D Koggalahewa, Y Xu, E Foo - Australasian Conference on Data Mining, 2021 - Springer
Spam detection in online social networks (OSNs) have become an immensely challenging
task with the nature and the use of online social networks. The spammers tend to change …

Detection and analysis of cryptocurrency scams on twitter

KK Chandra, K Kalla, J Bhatia, M Jayaprakash… - … on Algorithmic Aspects …, 2024 - Springer
With the increasing adoption of cryptocurrencies in finance, financial fraud has surged,
resulting in significant monetary losses. This paper presents a novel approach leveraging …