Mining the impact of social media information on public green consumption attitudes: a framework based on ELM and text data mining

This study endeavors to delve into public preferences surrounding green consumption, examining reasons for its low adoption using social media data. Employing the Elaboration Likelihood Model (ELM) and text data mining, it analyzes how information strategies from government, businesses, and media influence consumer attitudes toward green consumption. Findings reveal that women and individuals in economically developed regions show more concern for green consumption. The public responds positively to government policies and corporate actions but negatively to media campaigns. Engagement with information and emotional responses influence attitudes. The study offers strategies for policymakers and businesses to enhance consumer attitudes and behaviors toward green consumption and demonstrates an innovative integration of ELM with text data mining to monitor public attitude change, applicable beyond green consumption.

Jun Fan, Lijuan Peng, Tinggui Chen, Guodong Cong