ArticlePloS one2026
Spatiotemporal dynamics and forecasting of public attention to entrepreneurship education: An entropy-based modeling approach.
Article in PloS one, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Entrepreneurship education is increasingly important with the development of digital economy and post-pandemic. However, the distribution of public attention to entrepreneurship education (PAEE) remains unclear. Based on Baidu Index data from 2016 to 2024, this study first explores its spatiotemporal patterns. Then, an analytical framework based on Shannon and Tsallis entropy is established to analyze the spatial patterns, and a multi-model forecasting system combining SARIMA, LSTM, XGBoost, and other models is developed. The results show that PAEE shows a trend of continuous decrease, and the concentration in eastern provinces is stronger. Overall, hybrid models generally outperform single models, while the entropy-weighted ensemble demonstrates competitive performance by enhancing robustness and stability. The results of this study can provide quantitative reference for improving policies and promoting fair allocation of regional resources in entrepreneurship education. Meanwhile, this study offers a replicable framework to analyze patterned social behavior and forecasting trends in other fields.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.