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Published in 2024 at "Scientific Reports"
DOI: 10.1038/s41598-024-54809-z
Abstract: Message passing neural networks such as graph convolutional networks (GCN) can jointly consider various types of features for social bot detection. However, the expressive power of GCN is upper-bounded by the 1st-order Weisfeiler–Leman isomorphism test,…
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Keywords:
detection;
model;
bot detection;
subgraph ... See more keywords
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Published in 2022 at "IEEE Transactions on Information Forensics and Security"
DOI: 10.1109/tifs.2022.3170237
Abstract: This paper introduces a novel approach, inspired by the principles of Quantum Computing, to address web bot detection in terms of real-time classification of an incoming data stream of HTTP request headers, in order to…
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Keywords:
bot detection;
web bot;
quantum inspired;
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Published in 2023 at "IEEE Transactions on Information Forensics and Security"
DOI: 10.1109/tifs.2023.3254429
Abstract: While social bots can be used for various good causes, they can also be utilized to manipulate people and spread malware. Therefore, it is crucial to detect bots running on social media platforms. However, social…
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Keywords:
social bot;
based social;
architecture;
deep learning ... See more keywords
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Published in 2020 at "Communications of the ACM"
DOI: 10.1145/3409116
Abstract: Bots increasingly tamper with political elections and economic discussions. Tracing trends in detection strategies and key suggestions on how to win the fight.
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Keywords:
bot detection;
social bot;
detection;
decade social ... See more keywords
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Published in 2021 at "First Monday"
DOI: 10.5210/fm.v26i7.11474
Abstract: Social bots are automated accounts often involved in unethical or illegal activities. Academia has shown how these accounts evolve over time, becoming increasingly smart at hiding their true nature by disguising themselves as genuine accounts.…
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Keywords:
bot detection;
social bot;
coming age;
age adversarial ... See more keywords