Year: 2025
Type: article
Abstract: Twitter is a social network where users interact via text-based posts called tweets, using hashtags, mentions, shortened URLs, and retweets. The growing user base and open nature of Twitter have made it a target for automated programs, known as bots, which can be both beneficial and malicious. This research focuses on detecting and classifying Twitter accounts as human, bot, or cyborg. Given Twitter’s open nature, both helpful and harmful bots are prevalent, necessi- tating effective detection strategies. The study analyzes account behavior, content, and properties, introducing a classification system that integrates entropy analysis, spam detection, and account evaluation to improve user interaction transparency and platform security.
DOI: 10.55041/ijsrem43583
Authors: Arya Dhanesh, Jyothika K, Malavika Jayaraj, Nevin Jose Antony, Anu Treesa George
Institution: Vimal Jyothi Engineering College
Language: English
Topic: Spam and Phishing Detection
Subfield: Information Systems
Field: Computer Science
Domain: Physical Sciences
Open Access status: bronze
OpenAlex ID: W4409112262