Exploring public attention about green consumption on Sina Weibo: Using text mining and deep learning

Achieving the goal of carbon neutrality and carbon peak as scheduled puts forward new demands for the green transition of low-carbon lifestyle in Chinese society. In-depth practice of green consumption (GC) behavior can effectively promote the supply-side and consumption-side emission reduction work, but the phenomenon of high awareness, low practice is widespread in GC. The causes of consumers' low practice of GC need to be analyzed from the perspective of time and space from the actual media data. Furthermore, this process assists policymakers and stakeholders to understand the general attitude of the public towards GC, clarifying the propagation path of public emotions and the source of negative emotions. Based on the data from Sina Weibo, this paper applied text mining, a hybrid model of convolu-tional neural network and long and short-term memory neural network to analyze the public's attention, sentiment tendency and hot topics on GC. The results show that the vast majority of the Chinese public has a positive attitude toward GC; women and economically developed regions are more concerned about GC; the drivers of positive public sentiment toward GC include environmental awareness education, air pollution prevention and control, and online shopping; high green product prices, excessive time costs, chaotic sharing economy and one-size-fits-all solutions lead to negative public sentiment toward GC. By providing public sentiment analysis of GC, this research would assist decision-makers to understand the dissemination mechanism of public will in social media and clarify targeted solutions, which is of great significance for policy formulation and improvement.(c) 2021 Institution of Chemical Engineers. Published by Elsevier B.V. All rights reserved.

Automated summary

Achieving carbon neutrality and carbon peak on schedule poses new demands for the green transition of low-carbon lifestyle in Chinese society. In-depth practice of green consumption can effectively promote emission reduction, but high awareness and low practice are common in this area. This study analyzes public sentiment towards green consumption by examining social media data. The results show that the majority of Chinese public has a positive attitude towards green consumption, with women and economically developed regions showing greater interest. Positive sentiment is driven by environmental awareness education, air pollution prevention and control, and online shopping, while negative sentiment arises from high product prices, excessive time costs, a chaotic sharing economy, and one-size-fits-all solutions. These findings are significant for decision-makers to develop targeted solutions and improve policies.