Quantifying Impersonation on Social Media: Probability Assessment of Fake Accounts

Mary Likitha Swarup Reddy Gade, Mary Lohita Swarup Reddy Gade, J. Shobana, Eerla Siva Keerthi

2025

Abstract

This paper proposes a research work, to quantify impersonation on the social media platforms through evaluating the probabilities of the fake accounts. Building on this foundation, the study uses machine learning models, such as classifiers and anomaly detection algorithms, and network analysis techniques to explore features about behavioural patterns and structural attributes that can be used as distinguishing features between genuine and fake profiles. This approach aims to measure the likelihood of impersonation by analysing user activity, engagement patterns, and network connections. We validate this methodology through experimentation with various datasets that illustrate its effectiveness in detecting and estimating fake accounts on social media platforms. These insights not only help in understanding the impersonation dynamics but also provide a significant foundation for evaluating the likelihood of fake profiles that might help in paying more effective strategies to handle impersonation of users on such social platform.

Paper Citation

in Harvard Style

Gade M., Shobana J. and Keerthi E. (2025). Quantifying Impersonation on Social Media: Probability Assessment of Fake Accounts. In Proceedings of the 1st International Conference on Research and Development in Information, Communication, and Computing Technologies - ICRDICCT`25; ISBN 978-989-758-777-1, SciTePress, pages 425-431. DOI: 10.5220/0013884100004919

in Bibtex Style

@conference{icrdicct`2525,
author={Mary Gade and J. Shobana and Eerla Keerthi},
title={Quantifying Impersonation on Social Media: Probability Assessment of Fake Accounts},
booktitle={Proceedings of the 1st International Conference on Research and Development in Information, Communication, and Computing Technologies - ICRDICCT`25},
year={2025},
pages={425-431},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013884100004919},
isbn={978-989-758-777-1},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 1st International Conference on Research and Development in Information, Communication, and Computing Technologies - ICRDICCT`25
TI - Quantifying Impersonation on Social Media: Probability Assessment of Fake Accounts
SN - 978-989-758-777-1
AU - Gade M.
AU - Shobana J.
AU - Keerthi E.
PY - 2025
SP - 425
EP - 431
DO - 10.5220/0013884100004919
PB - SciTePress