NLP feature set variables for TwiBot-20.

<div><p>The study examines different graph-based methods of detecting anomalous activities on digital markets, proposing the most efficient way to increase market actors’ protection and reduce information asymmetry. Anomalies are defined below as both bots and fraudulent users (who can b...

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Main Author:	Agata Skorupka (20469080) (author)
Published:	2024
Subjects:	Cancer Science Policy Space Science Environmental Sciences not elsewhere classified Biological Sciences not elsewhere classified Mathematical Sciences not elsewhere classified Information Systems not elsewhere classified twitter social network significantly larger graphs reduce information asymmetry often means reducing nodes &# 8217 extract feature sets research examines whether real people ). detecting anomalous activities perform significantly better efficient method suitable bitcoin alpha ). better model performance anomaly detection models proposed algorithm based based statistics algorithm art graph embeddings efficient algorithm embeddings ). threat detection research proposes predictive performance new algorithm generated ). bitcoin otc art results efficient way based datasets based data using embeddings graph embeddings xlink "> text data study proves statistics result solution turned significant improvement scale well remain robust performing predictor one describing newest technologies methods based graph networks fraudulent users fraudulent transaction engineering overhead enabling modeling digital markets detecting anomalies computational efficiency based methods article proposes also yield adding even
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NLP feature set variables for TwiBot-20.

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