Growing Online Interest in ERNIE Bot Released Since 2022: An Analysis of Baidu Index Data
DOI:
https://doi.org/10.12775/PPS.2025.25.66078Keywords
search engine, Baidu index, ERNIE Bot, ChatGPT, data miningAbstract
Objective: Current evidence shows that since the launch of ERNIE (Enhanced Representation through kNowledge IntEgration) Bot, the public interest in it has been growing, which may have an impact in different fields. The purpose of this study is to quantitatively analyze the Baidu index of ERNIE Bot to reveal the public's attention to this technology and the trend of online search behavior in the past two years.
Methods: We used Baidu Index, a publicly available database to access query data in systematic and quantitative fashion, to search for key terms related to ERNIE Bot. We retrieved the search volume of two AI language models, ERNIE Bot and ChatGPT, extracted data over the time range from December 26, 2022(it is the inception of the comprehensive public release of large AI language models) to December 26, 2024. Results were given in search index.
Results: We observed that, since August 14, 2023, there has been a surge in public interest towards ERNIE Bot, preceded by fluctuations in this trend. Notably, this interest primarily dipped to its lowest ebb during traditional Chinese holidays, as well as winter and summer vacations. Compared with the same type of AI language model ChatGPT, the search interest of ERNIE Bot is significantly higher after August 14,2023.
Conclusion: The opening of ERNIE Bot to the public has sparked a notable increase in its visibility among the general populace. Its complimentary access, localized functionalities, and alignment with the educational requirements of the public have collectively sustained its search interest at an elevated level for an extended period. The escalating interest in ERNIE Bot among the public suggests a concurrent rise in market attention and user base, which is poised to foster its application across diverse domains such as education and enterprises. Consequently, this will generate a more diversified array of user needs and feedback.
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