Stabilizing a supervised bot detection algorithm: How much data is needed for consistent predictions?-Reference-Cited by-同舟云学术

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Stabilizing a supervised bot detection algorithm: How much data is needed for consistent predictions?

Published:2022-03 Issue: Volume:28 Page:100198
ISSN:2468-6964
Container-title:Online Social Networks and Media
language:en
Short-container-title:Online Social Networks and Media

Author:

Ng Lynnette Hui Xian^ORCID,Robertson Dawn C.^ORCID,Carley Kathleen M.^ORCID

Publisher

Elsevier BV

Subject

Computer Networks and Communications,Communication,Information Systems

Reference38 articles.

1. Deep neural networks for bot detection;Kudugunta;Inform. Sci.,2018

2. Automated diffusion? Bots and their influence during the 2016 U.S. presidential election;Boichak,2018

3. Bots fired: examining social bot evidence in online mass shooting conversations;Schuchard;Palgrave Commun.,2019

4. Analyzing the digital traces of political manipulation: The 2016 Russian interference Twitter campaign;Badawy,2018

5. Bots, elections, and social media: A brief overview;Ferrara,2020

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1. Analyzing digital propaganda and conflict rhetoric: a study on Russia’s bot-driven campaigns and counter-narratives during the Ukraine crisis;Social Network Analysis and Mining;2024-08-23

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3. What News Is Shared Where and How: A Multi-Platform Analysis of News Shared During the 2022 U.S. Midterm Elections;Social Media + Society;2024-04

4. Assembling a multi-platform ensemble social bot detector with applications to US 2020 elections;Social Network Analysis and Mining;2024-02-24

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