Fake Twitter(X) Profile Detection

Abstract

Individuals engage with social networking platforms for communication and interaction daily. People regularly create profiles on socials networking websites where users actively connect and interact. can connect and communicate with one another at any time and from anywhere. This has been a boon as well as a bane. People of all ages spend much of their time on social networking websites. This leads to the creation and sharing of massive volumes of data on social networks all around the world. These reasons have contributed to the rise of fake users who prey on other social network users. A fake user is the one who creates a profile under a pseudonym and false information. These profiles are created for satirical reasons, to deceive and spread fake news and misinformation. The user profiles on social networks need to be categorised into fake and real. The categorisation may enable us to access the actual user profiles. This study provides a classification technique for identifying false Twitter accounts based on various user features like account follower and following count, posted tweets, gender, etc. using different algorithms like, Random Forest, SVM etc. and measure its accuracy.