关键词: 生物多样性, 指数构建, 文本挖掘, 发展阶段, 应用前景

Abstract

Aim & Background: Given the growing societal awareness of biodiversity conservation, it is imperative to develop a biodiversity media attention index to scientifically evaluate the current status of biodiversity conservation, encourage public participation, optimize resource allocation, and facilitate the achievement of global biodiversity conservation objectives. 

Methods: We employed text mining technology to systematically screen keywords and develop the first China Biodiversity Media Attention Index (CBMAI). The index was constructed using reports from three authoritative news media outlets spanning 2013 to 2024. Its robustness and effectiveness were subsequently validated by varying the time intervals and comparing it with international indices. 

Results: (1) The CBMAI is closely linked to China's biodiversity conservation policies and significant events, accurately reflecting shifts in government and public attention. (2) The CBMAI can be divided into three stages: the rising stage, the consolidating stage, and the deepening stage. During the rising stage, the focus was primarily on policy preparation and planning. The consolidating stage saw accelerated policy implementation, transitioning from plan formulation to concrete execution. The deepening stage was marked by a significant increase in the frequency and broader scope of policies. 

Prospects: The CBMAI will provide valuable data support for policymaking, government regulation, enterprise risk management, scientific research, and investment decision-making.

Key words: Biodiversity, index construction, text mining, development phases, application prospects