This paper overcomes this limitation by presenting a comprehensive analysis for investigating the emotional landscape surrounding technology adoption by using the launch of ChatGPT as a case study.

This study proposes DroneLog, an interpretable framework for detecting anomalies and the severity levels on drone flight logs, using a multitask learning approach in a unified pipeline. Complying with the multitask learning nature, two target label representations are designed to leverage the shared low-level common features of the input messages over various severity levels.

This paper presents a data-driven analysis of the evolving landscape of DSbD from 2019 to 2024, gathering insights from textual documents referencing DSbD. Using a combination of text mining techniques and network analysis, a large corpus of textual documents was examined to identify key entities, including organisations, individuals, and the relationships between them.