Exploring public attention and sentiment toward carbon neutrality: evidence from Chinese social media Sina Weibo

Wang, Bo; Jiang, Zhong‐Ping; Cheng, Dawei; Wang, Ziao

doi:10.3389/fpsyg.2023.1200824

Cited by 3 publications

(1 citation statement)

References 47 publications

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“…The UNFCCC database is a very important climate change data resource that supports global climate change research and policy development. The database collects data through multiple channels, including national communications, country inventories, transparency reports submitted by governments, and relevant data published by other international agencies and research institutions (Wang et al, 2023a). The main purpose of the UNFCCC database is to provide information on climate change to the public, policymakers, and scientists.…”

Section: Datasetsmentioning

confidence: 99%

Study on the economic benefits of carbon-neutral digital platforms for sustainable development based on the GPT-QRCNN model

Yang,

Zhou

2023

Front. Ecol. Evol.

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IntroductionThis article proposes a method for assessing the economic benefits of carbon-neutral digital platforms, which promote sustainable development by reducing carbon emissions through digital technology and data platforms.MethodsThe proposed method combines the GPT (Generative Pre-trained Transformer) and QRCNN (Quantile Regression Convolutional Neural Network) models. Firstly, the GPT model is utilized to extract features from platform data. Then, these features are combined with the QRCNN model for sequence modeling, enhancing prediction accuracy and generalization ability.ResultsThe method's effectiveness is demonstrated through experimental verification using actual platform data. The results highlight the practical significance and application value of the proposed method in evaluating the economic benefits of carbon-neutral digital platforms.DiscussionBy leveraging digital technology and data platforms, carbon-neutral digital platforms aim to reduce carbon emissions and promote sustainable development. The proposed method provides a means to accurately predict and analyze the economic benefits associated with these platforms. The combination of the GPT and QRCNN models enhances the accuracy and generalization ability of economic benefit predictions, enabling informed decision-making and policy formulation.

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Section: Datasetsmentioning

confidence: 99%

Study on the economic benefits of carbon-neutral digital platforms for sustainable development based on the GPT-QRCNN model

Yang,

Zhou

2023

Front. Ecol. Evol.

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A time-frequency-based interval decomposition ensemble method for forecasting gasoil prices under the trend of low-carbon development

Yan,

Tian,

Sun

et al. 2024

Energy Economics

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Spatiotemporal dynamic and regional differences of public attention to vaccination: An empirical study in China

Zhang,

Guo,

2024

PLoS ONE

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Background Internet searches offer an indicator of public attention and possible demand for certain things. Studying the spatiotemporal characteristics of the public’s concern for vaccination can determine the spatiotemporal distribution of demand for vaccines in China, and capture the changes in the health awareness of the Chinese population, thus informing future vaccination strategies. Methods Based on the collection of Baidu search indices for vaccination-related keywords in 363 cities in China, This paper seeks to explore the spatiotemporal changes and regional differences in public attention toward vaccination in China by using the seasonal index, seasonal concentration index, Herfindahl index, Moran index, and Dagum Gini coefficient. Results The following findings are presented. First, there are significant seasonal fluctuations and unbalanced monthly distributions of vaccination-related public attention in China. Second, the public attention in Chinese cities shows the spatial characteristics of "leading in the east, followed by the central, western and northeastern regions". The spatial correlation of attention has been strengthened, and the high-high clusters are mainly distributed in the Beijing-Tianjin-Hebei (BTH), Yangtze River Delta (YRD), and Greater Bay Area (GBA) urban agglomerations. Third, regional differences in overall public attention narrowed in China, with intra-regional differences narrowing in seven regions (Northwest China, Central China, and so on), and intra-regional differences increasing in East China. The dominant role in the Gini coefficient changes from transvariation intensity to inter-regional differences. Conclusion Major public health emergencies stimulate the public’s attention to health topics. Although the short-term increase in vaccination-related public attention was not observed to translate into a long-term increase in public vaccine literacy, the seasonal and regional differences in vaccination-related public attention in China have significantly narrowed before and after COVID-19, suggesting that the imbalance between public health literacy levels has improved.

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Exploring public attention and sentiment toward carbon neutrality: evidence from Chinese social media Sina Weibo

Cited by 3 publications

References 47 publications

Study on the economic benefits of carbon-neutral digital platforms for sustainable development based on the GPT-QRCNN model

Study on the economic benefits of carbon-neutral digital platforms for sustainable development based on the GPT-QRCNN model

A time-frequency-based interval decomposition ensemble method for forecasting gasoil prices under the trend of low-carbon development

Spatiotemporal dynamic and regional differences of public attention to vaccination: An empirical study in China

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