Antonio Segura
Papers
1
Total Citations
3
H-Index
1
About
Antonio Segura is a researcher focused on the intersection of machine learning and social media security, with a particular emphasis on detecting automated accounts and mitigating online manipulation. His most-cited work, "Machine Learning Techniques to Evaluate Whether Twitter Accounts Are Human or Robot" (2020, 3 citations), addresses the growing threat of bot accounts designed to impersonate humans, distort public opinion, and exploit social platforms. By applying advanced machine learning models to analyze behavioral and content-based features, Segura has contributed to the development of more robust detection systems that help distinguish genuine users from automated agents. His research is especially relevant in an era where social media plays an increasingly central role in shaping discourse, and where malicious actors leverage bots for disinformation campaigns. While his citation count remains modest, Segura’s work represents a foundational step in a critical area of cybersecurity and digital ethics. His findings offer practical tools for platform moderators, policymakers, and researchers seeking to preserve the integrity of online spaces. For students and scholars entering this field, Segura’s research provides a clear, applied example of how machine learning can be harnessed to address real-world threats in social media environments.
Research Focus
Key Achievements
Top Papers
- 1