Results 31 to 40 of about 14,489,921 (146)

Experimental Evaluation: Can Humans Recognise Social Media Bots?

Big Data and Cognitive Computing
This paper aims to test the hypothesis that the quality of social media bot detection systems based on supervised machine learning may not be as accurate as researchers claim, given that bots have become increasingly sophisticated, making it difficult ...
Maxim Kolomeets, Olga Tushkanova, Vasily Desnitsky, Lidia Vitkova, Andrey Chechulin   +4 more
doaj   +1 more source

A Decade of Social Bot Detection

, 2020
In the aftermath of the 2016 US elections, the world started to realize the gravity of widespread deception in social media. Following Trump's exploit, we witnessed to the emergence of a strident dissonance between the multitude of efforts for detecting ...
S Cresci
core   +1 more source

Supplemental Material - Improving Social Bot Detection Through Aid and Training

, 2023
Supplemental Material for Improving Social Bot Detection Through Aid and Training by Ryan Kenny, Baruch Fischhoff, Alex Davis and Casey Canfield in Human ...
Casey Canfield (16641516), Baruch Fischhoff (133747), Alex Davis (7444508), Ryan Kenny (17398603)   +3 more
core   +1 more source

Identification of Spambots and Fake Followers on Social Network via Interpretable AI-Based Machine Learning

IEEE Access
Social networking platforms like X (Twitter) serve as hubs for open human interaction, but they are also increasingly infiltrated by automated accounts masquerading as human users.
Danish Javed, Noor Zaman Zaman, Navid Ali Khan, Sayan Kumar Ray, Arafat Al-Dhaqm, Victor R. Kebande   +5 more
doaj   +1 more source

Social Media Bot Detection using Dropout-GAN

, 2023
Bot activity on social media platforms is a pervasive problem, undermining the credibility of online discourse and potentially leading to cybercrime. We propose an approach to bot detection using Generative Adversarial Networks (GAN).
Jurecek, Martin, Shukla, Anant, Stamp, Mark   +2 more
core  

Unmasking social bots: how confident are we?

EPJ Data Science
Social bots remain a major vector for spreading disinformation on social media and a menace to the public. Despite the progress made in developing multiple sophisticated social bot detection algorithms and tools, bot detection remains a challenging ...
James Giroux, Gangani Ariyarathne, Alexander C. Nwala, Cristiano Fanelli   +3 more
doaj   +1 more source

Detecting Social Media Bots with Variational AutoEncoder and k-Nearest Neighbor

Applied Sciences, 2021
Malicious social media bots are disseminators of malicious information on social networks and seriously affect information security and the network environment.
Xiujuan Wang, Qianqian Zheng, Kangfeng Zheng, Yi Sui, Siwei Cao, Yutong Shi   +5 more
doaj   +1 more source

Social Media Bot Detection using Dropout-GAN [PDF]

Bot activity on social media platforms is a pervasive problem, undermining the credibility of online discourse and potentially leading to cybercrime. We propose an approach to bot detection using Generative Adversarial Networks (GAN).
Shukla, Anant
core   +1 more source

vamsitadikonda/chat-defender-bot: First Release

, 2022
The First release of the bot.
Bharath, hacker95-bot, Vamsi Tadikonda, bharathncsu, Swimitha, saisree44   +5 more
core   +1 more source

MRLBot: Multi-Dimensional Representation Learning for Social Media Bot Detection

, 2023
Social media bots pose potential threats to the online environment, and the continuously evolving anti-detection technologies require bot detection methods to be more reliable and general. Current detection methods encounter challenges, including limited
Yizhou Li, Yingjie Sun, Fanrui Zeng
core   +1 more source