Results 11 to 20 of about 14,489,921 (146)
Intention embedding method based social bot detection [PDF]
Tongxin xuebaoArtificial intelligence generated content technology has significantly enhanced the disguise capabilities of social bots, presenting new challenges to existing bot detection methods.
NIU Hongfeng +3 more
doaj +2 more sources
Social bot detection method based on fine-grained feature weighted expert network
大数据In recent years, research in the field of social bot detection has gradually evolved from individual feature analysis to group feature mining, and from traditional feature engineering to deep learning methods. Among them, graph network-based methods have
Zhang Huaibo +4 more
doaj +2 more sources
Improving Social Bot Detection Through Aid and Training. [PDF]
Hum Factors, 2023 Objective: We test the effects of three aids on individuals\u27 ability to detect social bots among Twitter personas: a bot indicator score, a training video, and a warning. Background: Detecting social bots can prevent online deception.
Kenny R +3 more
europepmc +2 more sources
Bert Model for Social Media Bot Detection [PDF]
, 2022 Millions of online posts about different topics and products are shared on popular social media platforms. One use of this content is to provide crowd-sourced information about a specific topic, event, or product.
Jones, James H Jr., Heidari, Maryam
core +1 more source
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 +1 more source
Bot, or not? Comparing three methods for detecting social bots in five political discourses
Big Data & Society, 2021 Social bots – partially or fully automated accounts on social media platforms – have not only been widely discussed, but have also entered political, media and research agendas. However, bot detection is not an exact science.
Franziska Martini +3 more
doaj +1 more source
johnchrishays/bot-detection: Initial release
, 2022 Code for "Simplistic Collection and Labeling Practices Limit the Utility of Benchmark Datasets for Twitter Bot ...
Chris Hays, Haoxaun "Orion545" Li
core +1 more source
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 +1 more source
Detecting bots in social-networks using node and structural embeddings
Journal of Big Data, 2023 Users on social networks such as Twitter interact with each other without much knowledge of the real-identity behind the accounts they interact with. This anonymity has created a perfect environment for bot accounts to influence the network by mimicking ...
Ashkan Dehghan +8 more
doaj +1 more source
Tweet-Based Bot Detection Using Big Data Analytics
IEEE Access, 2021 Twitter is one of the most popular micro-blogging social media platforms that has millions of users. Due to its popularity, Twitter has been targeted by different attacks such as spreading rumors, phishing links, and malware.
Abdelouahid Derhab +5 more
doaj +1 more source