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

被引:1
|
作者
Han, Kiuk [1 ]
Yeom, Jaesun [2 ]
Chung, Keunsuk [2 ]
机构
[1] Korea Maritime Inst, Fisheries Policy Implementat, Haeyang Ro 301 Gil 26, Busan 49111, South Korea
[2] Ulsan Natl Inst Sci & Technol, Sch Business Admin, 50 UNIST Gil, Ulsan 44919, South Korea
来源
APPLIED SCIENCES-BASEL | 2024年 / 14卷 / 05期
关键词
global issues; emerging issues; seafood; horizon scanning; text mining; FOOD SAFETY; INDICATORS;
D O I
10.3390/app14051820
中图分类号
O6 [化学];
学科分类号
0703 ;
摘要
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.
引用
收藏
页数:17
相关论文
共 50 条
  • [1] Identifying and Assessing Innovation Pathways for Emerging Technologies: A Hybrid Approach Based on Text Mining and Altmetrics
    Zhou, Xiao
    Guo, Ying
    Li, Fangshun
    Wang, Jin
    Wei, Huanan
    Yu, Miaomiao
    Chen, Siliang
    IEEE TRANSACTIONS ON ENGINEERING MANAGEMENT, 2021, 68 (05) : 1360 - 1371
  • [2] Industry 4.0: Emerging themes and future research avenues using a text mining approach
    Galati, Francesco
    Bigliardi, Barbara
    COMPUTERS IN INDUSTRY, 2019, 109 : 100 - 113
  • [3] Text Mining Approach for Identifying Product Ideas and Trends Based on Crowdfunding Projects
    Boye, David
    Ozcan, Sercan
    Fajana, Oluwatobi
    IEEE TRANSACTIONS ON ENGINEERING MANAGEMENT, 2023, (7112-7127) : 7112 - 7127
  • [4] A text mining approach to identifying sustainability in the private sector
    Spinder, Siemen
    Frasincar, Flavius
    Matsiiako, Vladyslav
    Boekestijn, David
    Brandt, Thomas
    COMPUTERS IN INDUSTRY, 2023, 149
  • [5] Using text mining algorithms in identifying emerging trends for recommender systems
    Raeesi Vanani I.
    Mahmoudi L.
    Jalali S.M.J.
    Pho K.-H.
    Quality & Quantity, 2022, 56 (3) : 1293 - 1326
  • [6] Ozone - an Emerging Technology for the Seafood Industry
    Goncalves, Alex Augusto
    BRAZILIAN ARCHIVES OF BIOLOGY AND TECHNOLOGY, 2009, 52 (06) : 1527 - 1539
  • [7] Text Mining-Based Approach for Identifying Critical Accident Causes in Highway Construction
    Do, Quan
    Le, Tuyen
    Le, Chau
    COMPUTING IN CIVIL ENGINEERING 2023-RESILIENCE, SAFETY, AND SUSTAINABILITY, 2024, : 1105 - 1112
  • [8] A Text Mining Approach for Sustainable Performance in the Film Industry
    Hwangbo, Hyunwoo
    Kim, Jonghyuk
    SUSTAINABILITY, 2019, 11 (11)
  • [9] Predicting emerging technologies with the aid of text-based data mining: the micro approach
    Smalheiser, NR
    TECHNOVATION, 2001, 21 (10) : 689 - 693
  • [10] Analysis of Insider Threats in the Healthcare Industry: A Text Mining Approach
    Lee, In
    INFORMATION, 2022, 13 (09)