Results 1 to 10 of about 14,489,921 (146)
FedKG: A Knowledge Distillation-Based Federated Graph Method for Social Bot Detection [PDF]
SensorsMalicious social bots pose a serious threat to social network security by spreading false information and guiding bad opinions in social networks. The singularity and scarcity of single organization data and the high cost of labeling social bots have ...
Xiujuan Wang +5 more
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SEGCN: a subgraph encoding based graph convolutional network model for social bot detection [PDF]
Scientific ReportsMessage 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 ...
Feng Liu +5 more
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CB-MTE: Social Bot Detection via Multi-Source Heterogeneous Feature Fusion [PDF]
SensorsSocial bots increasingly mimic real users and collaborate in large-scale influence campaigns, distorting public perception and making their detection both critical and challenging. Traditional bot detection methods, constrained by single-source features,
Meng Cheng +4 more
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Emoji-Driven Sentiment Analysis for Social Bot Detection with Relational Graph Convolutional Networks [PDF]
SensorsThe proliferation of malicious social bots poses severe threats to cybersecurity and social media information ecosystems. Existing detection methods often overlook the semantic value and emotional cues conveyed by emojis in user-generated tweets.
Kaqian Zeng, Zhao Li, Xiujuan Wang
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Identifying and Analyzing Bot-Generated Responses in Online Health Care Surveys: Methodological Study [PDF]
JMIR Medical InformaticsBackgroundThe increasing reliance on online surveys for collecting patient-reported feedback for health care research has led to growing concerns over fraudulent responses generated by bots.
Emily Hamovitch +2 more
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G-CutMix: A CutMix-based graph data augmentation method for bot detection in social networks. [PDF]
PLoS ONEThe CutMix technique is a sophisticated approach for augmenting data in order to train neural network-based image classifiers. Essentially, it involves cutting out a portion of a random image and pasting it into the same location as another image ...
Yan Li +4 more
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Neighborhood perceivable graph neural network for relational heterogeneous Twitter bot detection. [PDF]
PLoS ONEMalicious bots undermine the integrity and safety of online social platforms, making their detection an urgent priority. This work aims to address the limitations of existing GNN-based bot detection approaches, particularly their inability to adapt the ...
Yan Li, Haoyu Lu, Wanying Chen
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PLoS ONE, 2021 The participation of automated software agents known as social bots within online social network (OSN) engagements continues to grow at an immense pace.
Ross J Schuchard, Andrew T Crooks
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Applied Sciences, 2022 Twitter, as a popular social network, has been targeted by different bot attacks. Detecting social bots is a challenging task, due to their evolving capacity to avoid detection. Extensive research efforts have proposed different techniques and approaches
Eiman Alothali +3 more
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MethodsX, 2023 There has been a tremendous increase in the popularity of social media such as blogs, Instagram, twitter, online websites etc. The increasing utilization of these platforms have enabled the users to share information on a regular basis and also publicize
Monikka Reshmi Sethurajan +1 more
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