Results 71 to 80 of about 14,489,921 (146)

Supervised Machine Learning Bot Detection Techniques to Identify Social Twitter Bots [PDF]

, 2018
In this paper, we present novel bot detection algorithms to identify Twitter bot accounts and to determine their prevalence in current online discourse. On social media, bots are ubiquitous.
Proferes, Nicholas, Efthimion, Phillip George, Payne, Scott   +2 more
core   +1 more source

AN INVESTIGATION OF BOT ACCOUNT IDENTIFICATION ON TWITTER DATA

, 2021
Twitter bots are automated accounts which are programmed to perform certain tasks which resemble those of daily active users such as tweeting, liking a tweet or following.
Pasya, Nikitha
core  

Detection and impact estimation of social bots in the Chilean Twitter network

Scientific Reports
The rise of bots that mimic human behavior represents one of the most pressing threats to healthy information environments on social media. Many bots are designed to increase the visibility of low-quality content, spread misinformation, and artificially ...
Marcelo Mendoza, Eliana Providel, Marcelo Santos, Sebastián Valenzuela   +3 more
doaj   +1 more source

The build, operate, and transfer ("BOT") approach to infrastructure projects in developing countries [PDF]

Build, operate and transfer (BOT) projects are exceedingly complex from both a financial and a legal point of view. They require an extended period of time to develop and negotiate.
Augenblick, Mark, Custer, B. Scott
core  

Challenges in machine learning-based social bot detection: a systematic review

Discover Artificial Intelligence
The rise of social digital network platforms has led to the widespread presence of social bots, automated entities that actively engage with users and content.
Nasser Alkathiri, Khaled Slhoub
doaj   +1 more source

Profile-Free Behavioral Characterization of Bot-like Activity in a Political Reply Ecosystem on X: A Case Study

Information
Coordinated and bot-like activity on social media is usually studied with supervised detectors that need rich account data such as profiles, timelines, and follower networks, which is increasingly hard to obtain.
Kalin Kopanov, Tatiana Atanasova
doaj   +1 more source

Bot Detection in Social Media:An Empirical Study Using TwiBot-22

The proliferation of artificial accounts, usually referred to as “bots”, on social mediaplatforms poses major challenges to the authenticity and reliability of online discourse.Consequently, detecting and mitigating the influence of these bots has become
Sakhabutdinov, Irek
core   +2 more sources

DeBERTa-based framework for detecting machine-generated content on social media: a comparative study

Journal of Big Data
Machine-generated text, particularly deepfake content, presents substantial challenges for social media platforms. Detecting such content is crucial to maintaining trust and preventing misinformation.
Sara Sweidan, Norhan A. Farouk, Mohamed Abouhawwash, S. S. Askar, Mohamed Taha   +4 more
doaj   +1 more source

What Does the Bot Say? Opportunities and Risks of Large Language Models in Social Media Bot Detection [PDF]

Social media bot detection has always been an arms race between advancements in machine learning bot detectors and adversarial bot strategies to evade detection.
Wang, Ningnan, Feng, Shangbin, Tan, Zhaoxuan, Tsvetkov, Yulia, Wan, Herun, Luo, Minnan   +5 more
core   +1 more source

Multi-Strategy Improvement and Comparative Research on Data-Driven Social Network Construction in Edge-Deficient Scenarios for Social Bot Account Detection

Information
Accurate social bot detection relies on simulated data to alleviate the scarcity of labeled real-world datasets. Synthetic graph data serves as the core training resource for detection models within simulated data; nevertheless, edge deficiency in real ...
Junjie Wang, Minghu Tang
doaj   +1 more source