Learning textual features for Twitter spam detection: A systematic literature review

SB Abkenar, MH Kashani, M Akbari… - Expert Systems with …, 2023 - Elsevier
Background—Nowadays, with the rise of Internet access and mobile devices around the
globe, more people are using social networks for collaboration and receiving real-time …

Adaptive threshold optimisation for online feature selection using dynamic particle swarm optimisation in determining feature relevancy and redundancy

EAK Zaman, A Ahmad, A Mohamed - Applied Soft Computing, 2024 - Elsevier
In the era of data-driven decision-making, managing dynamic data streams characterised by
evolving data distributions and high dimensionality presents a formidable challenge for …

Metapath and syntax-aware heterogeneous subgraph neural networks for spam review detection

Z Zhang, Y Dong, H Wu, H Song, S Deng… - Applied Soft Computing, 2022 - Elsevier
Abstract Spam Review Detection is a subclass of text classification that aims to distinguish
genuine reviews from spam reviews (eg, irrelevant reviews, deceptive reviews, machine …

Adversarial machine learning on social network: A survey

S Guo, X Li, Z Mu - Frontiers in Physics, 2021 - frontiersin.org
In recent years, machine learning technology has made great improvements in social
networks applications such as social network recommendation systems, sentiment analysis …

The impact of the weighted features on the accuracy of X-platform's user credibility detection using supervised machine learning

NR Abid-Althaqafi, HA Alsalamah, WN Ismail - IEEE Access, 2024 - ieeexplore.ieee.org
Social media represent a vital actor in our lives, often serving as a primary source of
information, surpassing traditional sources. Among these platforms, the X-Platform, which …