• Govind Singh Mahara
• Sharad Gangele

This paper provides a comprehensive analysis of temporal anomalies in social networks. The study aims to develop a robust framework for detecting and characterizing anomalous events in the dynamic structure and content of social media data. The proposed methodology combines advanced techniques from network analysis, time series modeling, and machine learning to uncover patterns, trends, and outliers in the temporal evolution of social networks. Key findings reveal significant insights into the drivers, impacts, and implications of anomalous events, with applications in domains such as security, marketing, and public policy. This study contributes to the growing body of literature on social network dynamics and anomaly detection, offering a foundation for future research and practical interventions. By addressing the complexities of temporal dynamics and incorporating advanced analytical methodologies, the research underscores the transformative potential of anomaly detection in modern digital ecosystems ([1], [2]). Additionally, the findings highlight the importance of bridging theoretical insights with practical implementations to ensure broad applicability across diverse scenarios. By leveraging a multi- disciplinary approach, this study aims to inspire future innovations in anomaly detection and dynamic network analysis. Furthermore, the research illustrates the potential of temporal anomaly detection to reshape strategies for network optimization, enhance predictive capabilities, and foster proactive approaches in both public and private sectors. The discussion includes an exploration of how these insights can be integrated into scalable tools to address challenges across multiple domains.

Temporal Analysis of Anomalous Events in Social Networks

"Temporal Analysis of Anomalous Events in Social Networks", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.10, Issue 7, page no.k176-k183, July-2023, Available :http://www.jetir.org/papers/JETIR2307A25.pdf

"Temporal Analysis of Anomalous Events in Social Networks", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.10, Issue 7, page no. ppk176-k183, July-2023, Available at : http://www.jetir.org/papers/JETIR2307A25.pdf