Enhancing authenticity and trust in social media: an automated approach for detecting fake profiles
- Title
- Enhancing authenticity and trust in social media: an automated approach for detecting fake profiles
- Creator
- Unni M.V.; Jeevananda S.; Kalapurackal J.J.; Fatma S.
- Description
- Fake profile detection on social media is a critical task intended for detecting and alleviating the existence of deceptive or fraudulent user profiles. These fake profiles, frequently generated with malicious intent, could engage in different forms of spreading disinformation, online fraud, or spamming. A range of techniques is employed to solve these problems such as natural language processing (NLP), machine learning (ML), and behavioural analysis, to examine engagement patterns, user-generated content, and profile characteristics. This paper proposes an automated fake profile detection using the coyote optimization algorithm with deep learning (FPD-COADL) method on social media. This multifaceted approach scrutinizes user-generated content, engagement patterns, and profile attributes to differentiate genuine user accounts from deceptive ones, ultimately reinforcing the authenticity and trustworthiness of social networking platforms. The presented FPD-COADL method uses robust data pre-processing methods to enhance the uniformness and quality of data. Besides, the FPD-COADL method applies deep belief network (DBN) for the recognition and classification of fake accounts. Extensive experiments and evaluations on own collected social media datasets underscore the effectiveness of the approach, showcasing its potential to identify fake profiles with high scalability and precision. 2024 Institute of Advanced Engineering and Science. All rights reserved.
- Source
- Indonesian Journal of Electrical Engineering and Computer Science, Vol-35, No. 1, pp. 292-300.
- Date
- 2024-01-01
- Publisher
- Institute of Advanced Engineering and Science
- Subject
- Coyote optimization algorithm Deep belief network Deep learning Fake profile detection Social network
- Coverage
- Unni M.V., School of Business and Management, CHRIST (Deemed to be University), Bengaluru, India; Jeevananda S., School of Business and Management, CHRIST (Deemed to be University), Bengaluru, India; Kalapurackal J.J., School of Business and Management, CHRIST (Deemed to be University), Bengaluru, India; Fatma S., School of Business and Management, CHRIST (Deemed to be University), Bengaluru, India
- Rights
- All Open Access; Hybrid Gold Open Access
- Relation
- ISSN: 25024752
- Format
- Online
- Language
- English
- Type
- Article
Collection
Citation
Unni M.V.; Jeevananda S.; Kalapurackal J.J.; Fatma S., “Enhancing authenticity and trust in social media: an automated approach for detecting fake profiles,” CHRIST (Deemed To Be University) Institutional Repository, accessed February 25, 2025, https://archives.christuniversity.in/items/show/13060.