Robust Automated Monitoring of Dairy Cow Rumination via Improved YOLOv11 and BoT-SORT in Complex Environments. [PDF]
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HHG-Bot: A Hyperheterogeneous Graph-Based Twitter Bot Detection Model
IEEE Transactions on Computational Social SystemsDetecting Twitter bots is essential for combating misinformation and maintaining the integrity of online social networks. Existing methods often overlook the high-order interactions and heterogeneous relationships among users and tweets, limiting their ...
Tianbo Wang, Huacheng Li, Chunhe Xia
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Dispelling the Fake: Social Bot Detection Based on Edge Confidence Evaluation
IEEE Transactions on Neural Networks and Learning SystemsSocial bot detection is essential for maintaining the safety and integrity of online social networks (OSNs). Graph neural networks (GNNs) have emerged as a promising solution.
Songiln Hu, Shilong Li
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What Does the Bot Say? Opportunities and Risks of Large Language Models in Social Media Bot Detection [PDF]
Annual Meeting of the Association for Computational LinguisticsSocial media bot detection has always been an arms race between advancements in machine learning bot detectors and adversarial bot strategies to evade detection.
Shangbin Feng +5 more
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CGNN: A Compatibility-Aware Graph Neural Network for Social Media Bot Detection
IEEE Transactions on Computational Social SystemsWith the rise and prevalence of social bots, their negative impacts on society are gradually recognized, prompting research attention to effective detection and countermeasures. Recently, graph neural networks (GNNs) have flourished and have been applied
Fei-Yue Wang, Hu Tian, Daniel Zeng
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BeCAPTCHA-Mouse: Synthetic mouse trajectories and improved bot detection [PDF]
Pattern Recognition, 2022 We first study the suitability of behavioral biometrics to distinguish between computers and humans, commonly named as bot detection. We then present BeCAPTCHA-Mouse, a bot detector based on: i) a neuromotor model of mouse dynamics to obtain a novel ...
Ruben Vera-Rodriguez +2 more
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BotMoE: Twitter Bot Detection with Community-Aware Mixtures of Modal-Specific Experts
Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, 2023Twitter bot detection has become a crucial task in efforts to combat online misinformation, mitigate election interference, and curb malicious propaganda.
Yuhan Liu +5 more
semanticscholar +1 more source
As malicious actors employ increasingly advanced and widespread bots to disseminate misinformation and manipulate public opinion, the detection of Twitter bots has become a crucial task.
Zijian Cai +6 more
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Over-Sampling Strategy in Feature Space for Graphs based Class-imbalanced Bot Detection
The Web Conference, 2023The presence of a large number of bots in Online Social Networks (OSN) leads to undesirable social effects. Graph neural networks (GNNs) are effective in detecting bots as they utilize user interactions.
S. Shi +5 more
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Friendship Preference: Scalable and Robust Category of Features for Social Bot Detection
IEEE Transactions on Dependable and Secure Computing, 2023Social bots are intelligent programs that control the behavior of fake accounts in an online social network(OSN). They pass themselves off as human accounts and manipulate the health of the ecosystem of OSNs.
Samaneh Hosseini Moghaddam, M. Abbaspour
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