On the public citation graph
AI-Generated Spam Review Detection Framework with Deep Learning Algorithms and Natural Language Processing
0 signed · 54 inferred · view as graph
Inferred edges come from two machine sources: sweeps of open repository metadata (mostly SSRN and Zenodo), and a bulk OpenAlex citation snapshot. Every row below is labelled with the one it came from. Neither is a complete citation index — absence here is not evidence of absence.
Is this your work? Sign in with ORCID and put your name on the
claims that are yours.
Reference health. See whether every reference in this work resolves to a
known work and none has been retracted — and get a dated CiteStamped
badge you can embed.
What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1002/spy2.9openalex-snapshot
Detecting opinion spams and fake news using text classification
inferredcites →https://doi.org/10.1007/978-3-030-19823-7_28openalex-snapshot
Review Spam Detection Using Word Embeddings and Deep Neural Networks
inferredcites →https://doi.org/10.1007/s11023-020-09548-1openalex-snapshot
GPT-3: Its Nature, Scope, Limits, and Consequences
inferredcites →https://doi.org/10.1016/j.annals.2015.12.019openalex-snapshot
What makes an online consumer review trustworthy?
inferredcites →https://doi.org/10.1016/j.jbusres.2018.12.009openalex-snapshot
Illusions of truth—Experimental insights into human and algorithmic detections of fake online reviews
inferredcites →https://doi.org/10.1016/j.jksuci.2018.10.014openalex-snapshot
Mutual clustering coefficient-based suspicious-link detection approach for online social networks
inferredcites →https://doi.org/10.1016/j.jretconser.2017.04.005openalex-snapshot
Incentivized reviews: Promising the moon for a few stars
inferredcites →https://doi.org/10.1016/j.jretconser.2018.12.006openalex-snapshot
Unfolding the characteristics of incentivized online reviews
inferredcites →https://doi.org/10.1016/j.jretconser.2021.102771openalex-snapshot
Creating and detecting fake reviews of online products
inferredcites →https://doi.org/10.1016/j.neucom.2018.04.074openalex-snapshot
Towards automatic filtering of fake reviews
inferredcites →https://doi.org/10.1109/access.2021.3049626openalex-snapshot
A Novel Deep Learning-Based Multilevel Parallel Attention Neural (MPAN) Model for Multidomain Arabic Sentiment Analysis
inferredcites →https://doi.org/10.1109/access.2021.3050547openalex-snapshot
Citation Intent Classification Using Word Embedding
inferredcites →https://doi.org/10.1109/comsnets.2019.8711124openalex-snapshot
Analyzing Real and Fake users in Facebook Network based on Emotions
inferredcites →https://doi.org/10.1109/sieds58326.2023.10137767openalex-snapshot
Distinguishing Human-Written and ChatGPT-Generated Text Using Machine Learning
inferredcites →https://doi.org/10.1145/1039621.1039625openalex-snapshot
An evaluation of statistical spam filtering techniques
inferredcites →https://doi.org/10.1145/2487575.2487688openalex-snapshot
Synthetic review spamming and defense
inferredcites →https://doi.org/10.1145/2740908.2742570openalex-snapshot
Detecting Singleton Review Spammers Using Semantic Similarity
inferredcites →https://doi.org/10.1145/2912845.2912868openalex-snapshot
Capturing Word Choice Patterns with LDA for Fake Review Detection in Sentiment Analysis
inferredcites →https://doi.org/10.1186/s40537-015-0029-9openalex-snapshot
Survey of review spam detection using machine learning techniques
inferredcites →https://doi.org/10.1609/icwsm.v7i1.14389openalex-snapshot
What Yelp Fake Review Filter Might Be Doing?
inferredcites →https://doi.org/10.18653/v1/2023.ijcnlp-main.40openalex-snapshot
ConDA: Contrastive Domain Adaptation for AI-generated Text Detection
inferredcites →https://doi.org/10.18653/v1/p19-3019openalex-snapshot
GLTR: Statistical Detection and Visualization of Generated Text
inferredcites →https://doi.org/10.2196/48904openalex-snapshot
Differentiating ChatGPT-Generated and Human-Written Medical Texts: Quantitative Study
inferredcites →https://doi.org/10.3390/computers12060126openalex-snapshot
Arabic Sentiment Analysis Based on Word Embeddings and Deep Learning
inferredcites →https://doi.org/10.3390/math11153400openalex-snapshot
Differentiating Chat Generative Pretrained Transformer from Humans: Detecting ChatGPT-Generated Text and Human Text Using Machine Learning
inferredcites →https://doi.org/10.5555/1248547.1248644openalex-snapshot
Spam Filtering Using Statistical Data Compression Models
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
inferred← citeshttps://doi.org/10.1007/978-3-032-11426-6_4openalex-snapshot
Harnessing Artificial Intelligence for the Detection and Analysis of Microplastics and Associated Chemicals in the Atmosphere
inferred← citeshttps://doi.org/10.1007/978-3-032-22196-4_8openalex-snapshot
Machine and Deep Learning for AI Text Detection
inferred← citeshttps://doi.org/10.1016/j.inffus.2026.104715openalex-snapshot
A survey on fake review detection: From pre-trained language models to large language models
inferred← citeshttps://doi.org/10.1016/j.microc.2025.114624openalex-snapshot
A novel dynamic analysis method for shortening detection time of lateral flow immunoassay through time series forecasting
inferred← citeshttps://doi.org/10.1080/13614568.2026.2682124openalex-snapshot
Detection of spam webpages using a new improved H-index centrality and weighted H-index centrality
inferred← citeshttps://doi.org/10.1108/ijicc-10-2025-0655openalex-snapshot
Research on Chinese multimodal fake review detection for AIGC-Generated content
inferred← citeshttps://doi.org/10.1109/3ict68299.2025.11442128openalex-snapshot
Conceptualizing Authenticity in Generative AI-Driven E-Learning: A Critical Examination of Generative Artificial Intelligence in Educational Systems
inferred← citeshttps://doi.org/10.1109/access.2025.3532611openalex-snapshot
UEF-HOCUrdu: Unified Embeddings Ensemble Framework for Hate and Offensive Text Classification in Urdu
inferred← citeshttps://doi.org/10.1109/csecs64665.2025.11009627openalex-snapshot
Data Quality-Aware Federated Learning for Fake Review Detection
inferred← citeshttps://doi.org/10.1109/iaict65714.2025.11101496openalex-snapshot
Two Stage Framework of Spam Detection for TikTok Reviews on Google Play Store
inferred← citeshttps://doi.org/10.1109/ic366947.2025.11290561openalex-snapshot
Unmasking AI-Generated Fake Reviews Using Transformers Stacking Ensemble : BRoDD
inferred← citeshttps://doi.org/10.1109/iccsdfai70505.2026.11647981openalex-snapshot
Integration of Blockchain Technology into a Correspondence Analysis Service for Ensuring Digital Evidence Integrity in Forensics
inferred← citeshttps://doi.org/10.1109/icei65890.2026.11448007openalex-snapshot
Spam Detection in Text Messages and Emails: A Natural Language Processing Approach
inferred← citeshttps://doi.org/10.1109/icesst69086.2026.11582880openalex-snapshot
Intelligent Fake Review Detection Using DistilBERT with BiLSTM and it's Behavioural Features
inferred← citeshttps://doi.org/10.1109/iciiet65921.2025.11379351openalex-snapshot
Natural Language Processing Framework for Secure Social Media Content Filtering and Sentiment Detection
inferred← citeshttps://doi.org/10.1109/itis67966.2025.11309139openalex-snapshot
SMSHIELD: A Real-Time Smishing Detection in Mobile Messaging Systems using Deep Learning Approach
inferred← citeshttps://doi.org/10.1109/sist61657.2025.11139296openalex-snapshot
Text Classification for AI Generated Content with Machine Learning and Deep Learning Models
inferred← citeshttps://doi.org/10.1145/3787279.3787313openalex-snapshot
Can Naive Bayes Still Catch Spam A Study on AI-Modified Emails
inferred← citeshttps://doi.org/10.3389/fdata.2026.1948398openalex-snapshot
Big data analytics and sentiment analysis for health misinformation detection: a systematic literature review of influencing factors, implementation challenges and a data-driven adoption framework
inferred← citeshttps://doi.org/10.3390/app152312662openalex-snapshot
Natural Language Processing in Generating Industrial Documentation Within Industry 4.0/5.0
inferred← citeshttps://doi.org/10.3390/app16052263openalex-snapshot
Deep Learning for e-Commerce: Recent Developments in Prediction, Personalization and Decision Intelligence
inferred← citeshttps://doi.org/10.4018/979-8-3693-2935-1.ch005openalex-snapshot
Enlarged Artificial intelligence and Deep Learning in Big Data Analytics and Intelligent Interactive Multimedia Systems for m-Healthcare Applications
inferred← citeshttps://doi.org/10.48084/etasr.13369openalex-snapshot
Detecting Sophisticated Fake Reviews on E-Commerce Platforms Using Adversarial Transformer Networks
Editorial review for independent work. ICSAC — the Institute for Complexity
Science and Advanced Computing — runs a structured editorial panel for researchers
publishing outside journals, and publishes on CiteStamp rails. Submission is free
and goes through ORCID: icsacinstitute.org/submit.