Real-Time Twitter Spam Detection and Sentiment Analysis using Machine Learning and Deep Learning Techniques

Machine Learning Techniques for Spam Detection in Email and IoT Platforms: Analysis and Research Challenges

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A systematic literature review on spam content detection and classification

(2022) Sanaa Kaddoura et al.   PeerJ Computer Science

A Combined Text-Based and Metadata-Based Deep-Learning Framework for the Detection of Spam Accounts on the Social Media Platform Twitter

(2022) Atheer S. Alhassun et al.   Processes

Multi-objective cluster head selection using fitness averaged rider optimization algorithm for IoT networks in smart cities

(2021) Mamoun Alazab et al.   Sustainable Energy Technologies and Assessments

An ensemble machine learning approach through effective feature extraction to classify fake news

(2020) Saqib Hakak et al.   Future Generation Computer Systems-The International Journal of eScience

Sentiment analysis and opinion mining applied to scientific paper reviews

(2019) Brian Keith Norambuena et al.   Intelligent Data Analysis

Unsupervised collective-based framework for dynamic retraining of supervised real-time spam tweets detection model

(2019) Mahdi Washha et al.   EXPERT SYSTEMS WITH APPLICATIONS

A domain transferable lexicon set for Twitter sentiment analysis using a supervised machine learning approach

(2018) M. Ghiassi et al.   EXPERT SYSTEMS WITH APPLICATIONS

Ranking Analysis for Online Customer Reviews of Products Using Opinion Mining with Clustering

(2018) S. K. Lakshmanaprabu et al.   COMPLEXITY

Detection of spam-posting accounts on Twitter

(2018) Isa Inuwa-Dutse et al.   NEUROCOMPUTING