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.
1 of the 41 references listed on this page is in the Retraction Watch database as retracted (export 2026-10-21): 10.1007/s11042-019-7301-5 (notice 2022-09-13).
Dataset join, best-effort; this page does not check the publisher record.
Retraction Watch data via Crossref Labs, used with credit; OpenCitations Index (CC0) and Meta (CC BY 4.0);
dataset doi:10.7910/DVN/WT8VOA (CC BY 4.0).
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RETRACTED ARTICLE: Automatic detection of lung cancer from biomedical data set using discrete AdaBoost optimized ensemble learning generalized neural networks
Demystifying the Role of Natural Language Processing (NLP) in Smart City Applications: Background, Motivation, Recent Advances, and Future Research Directions
A review of fake news detection approaches: A critical analysis of relevant studies and highlighting key challenges associated with the dataset, feature representation, and data fusion
An Evaluation of Automation on Misogyny Identification(AMI) and Deep-Learning Approaches for Hate Speech -Highlight on Graph Convolutional Networks and Neural Networks
Deep-Cov19-Hate: A Textual-Based Novel Approach for Automatic Detection of Hate Speech in Online Social Networks throughout COVID-19 with Shallow and Deep Learning Models
POSSIBLE OPTIONS FOR IMPROVING EXISTING APPROACHES TO FAKE NEWS DETECTION BASED ON USING THE POTENTIAL OF MACHINE AND DEEP LEARNING ALGORITHMS, SENTIMENT OF NEWS CONTENT AND EMOTIONS IN USER COMMENTS
How to Detect Online Hate towards Migrants and Refugees? Developing and Evaluating a Classifier of Racist and Xenophobic Hate Speech Using Shallow and Deep Learning
Machine Learning Approach to Determine the Impact of Hate Speech Based on Public Opinions
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