Results 51 to 60 of about 7,753,315 (190)
Scalable and Generalizable Social Bot Detection through Data Selection [PDF]
AAAI Conference on Artificial Intelligence, 2019 Efficient and reliable social bot classification is crucial for detecting information manipulation on social media. Despite rapid development, state-of-the-art bot detection models still face generalization and scalability challenges, which greatly limit
Kai-Cheng Yang +3 more
semanticscholar +1 more source
Bot Datasets on Twitter: Analysis and Challenges
Applied Sciences, 2021 The reach and influence of social networks over modern society and its functioning have created new challenges and opportunities to prevent the misuse or tampering of such powerful tools of social interaction.
Luis Daniel Samper-Escalante +3 more
doaj +1 more source
Efficient Deep Learning Bot Detection in Games Using Time Windows and Long Short-Term Memory (LSTM)
IEEE Access, 2020 Bots in video games has been gaining the interest of industry as well as academia as a problem that has been enabled by the recent advances in deep learning and reinforcement learning.
Michail Tsikerdekis +5 more
doaj +1 more source
Enhancing misinformation countermeasures: a multimodal approach to twitter bot detection
Social Network Analysis and MiningIdentifying bots on X (formerly Twitter) is essential for preventing misinformation and ensuring user safety. However, current models face several challenges: (i) the use of outdated techniques and attributes, particularly those trained on older datasets;
Olmar Arranz-Escudero +2 more
semanticscholar +1 more source
Experimental Evaluation: Can Humans Recognise Social Media Bots?
Big Data and Cognitive ComputingThis paper aims to test the hypothesis that the quality of social media bot detection systems based on supervised machine learning may not be as accurate as researchers claim, given that bots have become increasingly sophisticated, making it difficult ...
Maxim Kolomeets +4 more
doaj +1 more source
EPJ Data ScienceSocial bots pose a significant threat to online platforms, demanding robust methods to detect their increasingly complex behaviors. This paper introduces MM-HGT-Bot, a multi-modal framework that advances the field by operationalizing social network ...
Jian-Hong Luo, Chao Jin
semanticscholar +1 more source
Spatial Game Signatures for Bot Detection in Social Games
, 2021 Bot detection is an emerging problem in social games that requires different approaches from those used in massively multi-player online games (MMOGs). We focus on mouse selections as a key element of bot detection.
Jiang, Xuxian +3 more
core +1 more source
On the Accuracy of Bot Detection Techniques [PDF]
, 2022 peer reviewedDevelopment bots are often used to automate a wide variety of repetitive tasks in collaborative software development. Such bots are commonly among the most active project contributors in terms of commit activity.
Golzadeh, Mehdi +2 more
core +1 more source
Journal of Advanced Research in Natural and Applied Sciences, 2023 The use of social media as a news source is quite common today. However, the fact that the news encountered on social media are accepted as true without questioning or checking their validity is one of the main reasons for the dissemination of fake news.
Maide Feyza Er, Yonca Bayrakdar Yılmaz
doaj +1 more source
HOVER: Homophilic Oversampling via Edge Removal for Class-Imbalanced Bot Detection on Graphs
International Conference on Information and Knowledge Management, 2023 As malicious bots reside in a network to disrupt network stability, graph neural networks (GNNs) have emerged as one of the most popular bot detection methods. However, in most cases these graphs are significantly class-imbalanced. To address this issue,
Bradley Ashmore, Lingwei Chen
semanticscholar +1 more source