Identifying Emerging Issues in the Seafood Industry Based on a Text Mining Approach

Abstract

Identification of emerging issues has garnered growing interest as a way to establish proactive policy formulation. However, in fisheries research, analyzing such issues has largely depended on the literature or researchers’ judgment. We use keyword analysis, targeting news application programming interfaces (News APIs) (72,981 news sources and blogs), to investigate issues in the global seafood industry from January 2019 to March 2022. Among a variety of topics identified by year and country, in general, seafood market function, health, and tariffs were the main issues in 2019, while COVID-19-related issues were primarily mentioned between 2020 and 2021. After 2022, the role of the market regained attention, and various new issues rose to the surface. To identify emerging issues, we jointly employ dynamic time warping (DTW) and growth models, which derive several keywords, including coercion, cuisines, food safety, ketones, plastic ingestions, seafood alcohol, urbanization, wastewater treatment, and the World Trade Organization (WTO). High interest in food safety, environmental change, trade conflict, and seafood value improvement reveal the need for proper policy responses.

Keywords

• global issues
• emerging issues
• seafood
• horizon scanning
• text mining