SeBot-MLS: Multi-level structural feature learning for graph-based social bot detection
Journal of Safety Science and ResilienceRecent advances in artificial intelligence technologies, especially large language models, have made social bots more intelligent and human-like. This increased sophistication poses significant challenges to accurate bot detection.
Xinyi Tian, Yuqi He, Yimei Wu, Xin Lu
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The build, operate, and transfer ("BOT") approach to infrastructure projects in developing countries [PDF]
Build, operate and transfer (BOT) projects are exceedingly complex from both a financial and a legal point of view. They require an extended period of time to develop and negotiate.
Augenblick, Mark, Custer, B. Scott
core
Enhanced bot detection on twibot-20 dataset
Bot detection is critical in safeguarding social networks against malicious activities such as propagating misinformation and shaping public opinion. Twitter, being extensively studied due to its accessibility and interactive nature, serves as an ideal ...
Çakir, S.U. +2 more
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Improving Bot Response Contradiction Detection via Utterance Rewriting
, 2022 Though chatbots based on large neural models can often produce fluent responses in open domain conversations, one salient error type is contradiction or inconsistency with the preceding conversation turns.
Jin, Di +3 more
core
Hybrid whale-gray wolf optimization for efficient intrusion detection in the Internet of Things
Journal of Engineering and Applied ScienceThe extensive implementation of the Internet of Things (IoT) has transformed how mobile devices transmit data and facilitates communication and automation among interoperable items.
Xin Jin, He Deng, Xin Jiao
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BotSCG: Twitter Bot Detection With Semantic Consistency and Dual-Modulated Graph Learning
IEEE AccessTwitter bot detection has emerged as a critical yet challenging task for preventing public opinion manipulation and ensuring the authenticity of online interactions.
Chunling Wu +3 more
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Social bot detection method based on fine-grained feature weighted expert network
大数据In recent years, research in the field of social bot detection has gradually evolved from individual feature analysis to group feature mining, and from traditional feature engineering to deep learning methods. Among them, graph network-based methods have
Zhang Huaibo +4 more
doaj
(Un)Trendy Japan: Twitter bots and the 2017 Japanese general election
Politics in Central Europe, 2019 Social networking services (SNSs) can significantly impact public life during important political events. Thus, it comes as no surprise that different political actors try to exploit these online platforms for their benefit.
Mintal Jozef Michal, Vancel Róbert
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IoT intrusion detection system based on machine learning and deep learning
Iraqi Journal for Computers and InformaticsThe proliferation of Internet of Things IoT devices has amplified cybersecurity challenges, necessitating robust Intrusion Detection Systems IDS to safeguard against threats such as botnets and Distributed Denial-of-Service DDoS attacks.
karrar Majid Jasim, Joolan Rokan Nayef
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GANBOT: a GAN-based framework for social bot detection. [PDF]
Soc Netw Anal Min, 2022 Najari S, Salehi M, Farahbakhsh R.
europepmc +1 more source