Abstract:
The growth of social media platforms has allowed people to connect and interact in ways that were unimaginable in the past. However, it has also led to an increase in fraudulent information, which poses a serious problem for the integrity of the platform and user trust. This research paper provides an in-depth review of current practices and strategies, focusing on the key elements of identifying fake profileson social media. The presence of misinformation can be detected and mitigated using various detection methods developed from machine learning, data miningand network analysis. A discussion of metrics and data provides insight into how the discovery algorithm works.The report addresses issues such as attacks, enforcementand privacy concerns while recommending future research opportunities for enhanced detection. The results and recommendations presented here aim to help develop robust and practical solutions to the widespread fraud problem on social media platforms, thereby creating a safer and more secure online experience.
