The temporal characteristics of online interest in after-school services: An Analysis of Baidu Index Data
DOI:
https://doi.org/10.12775/PPS.2025.24.64298Keywords
After-school services, Search engine, Baidu Index, Big data, Temporal trendsAbstract
Aim. This study aims to systematically quantify and analyze the temporal evolution of public online search behaviors regarding after-school services since the implementation of the Double Reduction policy. By thoroughly exploring the changing characteristics of public interest, the study seeks to reveal the potential impact of policy implementation on societal educational demands, providing data support and decision-making references for the optimization and implementation of education policies.
Methods. The Baidu Index is a publicly accessible database that accesses search query data in a systematic and quantitative manner for searches for after-school services as key terms. We queried the search volume for after-school services, identified the most commonly used terms, and extracted data from the China for the period between July 1, 2021 and June 30, 2025.
Results. The study results show that in September 2021, when the Double Reduction policy began to be implemented across China, searches for the term after-school services peaked, followed by a downward trend. Public interest in the term was higher during the school season and lower during the winter and summer vacations.
Conclusions. The implementation of the after-school services policy has indeed brought convenience to the public, increased opportunities for student participation in activities, and promoted the holistic development of students. To better advance this policy, further optimization is needed to align with the United Nations' Sustainable Development Goals (SDGs).
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