Unlocking the potential of news: A systematic review of advantages and challenges for event detection and analysis

Abstract

Social media platforms, including both social networks and news outlets, have been widely utilized for event detection and analysis tasks. While social networks constitute the most commonly used data source due to their high volume and immediacy, news articles offer distinctive advantages such as access to well-structured historical archives and the availability of more coherent, detailed narratives, which can enhance the reliability and interpretability of event-related insights. In this study, we conduct a review and highlight key considerations that should be addressed when developing event detection applications based on news data sources. In our systematic review, we retrieved 654 papers from 2019 until 2024, covering four digital libraries (Springer Link, Science Direct from Elsevier, ACM, IEEE Explore). After applying exclusion criteria, we analyzed 79 papers qualitatively and quantitatively. We aimed to answer the following research questions: What is the motivation for using news data? What is the time span of the analyzed events? How detailed can the information be extracted? What are the most commonly used techniques and evaluation metrics? Based on the results, we identified several use cases where news is the most effective source of data in terms of the amount of information that can be retrieved, the quality of the content, and the response time, which can be as fast as social networks in some situations. Finally, we presented some challenges and opportunities in the area.