Supervised learning models for social bot detection: Literature review and benchmark-Reference-Cited by-同舟云学术

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Supervised learning models for social bot detection: Literature review and benchmark

Published:2024-03 Issue: Volume:238 Page:122217
ISSN:0957-4174
Container-title:Expert Systems with Applications
language:en
Short-container-title:Expert Systems with Applications

Author:

Nguyen Hoang-Dung^ORCID,Nguyen Duc Q.^ORCID,Nguyen Cong-Duy^ORCID,To Phong T.,Nguyen Danh H.^ORCID,Nguyen-Gia Huy^ORCID,Tran Long H.,Tran Anh Q.,Dang-Hieu An^ORCID,Nguyen-Duc Anh^ORCID,Quan Tho^ORCID

Funder

Viet Nam National University Ho Chi Minh City

Publisher

Elsevier BV

Subject

Artificial Intelligence,Computer Science Applications,General Engineering

Reference50 articles.

1. Twitter turing test: Identifying social machines;Alarifi;Information Sciences,2016

2. Detecting social bots on Twitter: A literature review;Alothali,2018

3. Sentiment analysis: Adjectives and adverbs are better than adjectives alone.;Benamara;ICWSM,2007

4. Its all in a name: detecting and labeling bots by their name;Beskow;Computational and Mathematical Organization Theory,2019

5. Language models are few-shot learners;Brown,2020

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