Balancing Security and Privacy: Web Bot Detection, Privacy Challenges, and Regulatory Compliance under the GDPR and AI Act [version 1; peer review: 2 approved] [PDF]
Open Research EuropeThis paper presents a comprehensive analysis of web bot activity, exploring both offensive and defensive perspectives within the context of modern web infrastructure.
Javier Martínez Llamas +3 more
doaj +3 more sources
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
doaj +3 more sources
Insights into elections: An ensemble bot detection coverage framework applied to the 2018 U.S. midterm elections. [PDF]
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
doaj +2 more sources
DeeProBot: a hybrid deep neural network model for social bot detection based on user profile data. [PDF]
Soc Netw Anal Min, 2022 Use of online social networks (OSNs) undoubtedly brings the world closer. OSNs like Twitter provide a space for expressing one’s opinions in a public platform.
Hayawi K +4 more
europepmc +2 more sources
Unsupervised Social Bot Detection via Structural Information Theory [PDF]
ACM Transactions on Information SystemsResearch on social bot detection plays a crucial role in maintaining the order and reliability of information dissemination while increasing trust in social interactions. The current mainstream social bot detection models rely on black-box neural network
Hao Peng, Philip S. Yu, Zhengtao Yu
exaly +2 more sources
Creating a Bot-tleneck for malicious AI: Psychological methods for bot detection. [PDF]
Behav Res MethodsThe standard approach for detecting and preventing bots from doing harm online involves CAPTCHAs. However, recent AI research, including our own in this manuscript, suggests that bots can complete many common CAPTCHAs with ease.
Rodriguez C, Oppenheimer DM.
europepmc +2 more sources
An Evolutionary Computation Approach for Twitter Bot Detection
Applied Sciences, 2022 Bot accounts are automated software programs that act as legitimate human profiles on social networks. Identifying these kinds of accounts is a challenging problem due to the high variety and heterogeneity that bot accounts exhibit.
Luigi Rovito +3 more
doaj +3 more sources
Twitter Bot Detection Using Neural Networks and Linguistic Embeddings
IEEE Open Journal of the Computer Society, 2023 Twitter is a web application playing the dual role of online social networking and micro-blogging. The popularity and open structure of Twitter have attracted a large number of automated programs, known as bots.
Feng Wei, Uyen Trang Nguyen
doaj +2 more sources
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
doaj +2 more sources
Social media bot detection with deep learning methods: a systematic review
Neural Computing and Applications, 2023 Social bots are automated social media accounts governed by software and controlled by humans at the backend. Some bots have good purposes, such as automatically posting information about news and even to provide help during emergencies.
Sujith Samuel Mathew +2 more
exaly +2 more sources