Global trends in green consumption: analyzing market acceptance and sentiment through Instagram data mining

Abstract

This study explores into the dynamics of global consumer sentiment towards green products, leveraging a dataset of 109,417 Instagram comments to uncover the attributes that drive discussions and evaluations of sustainability on social media. By employing a multifaceted analytical approach that includes sentiment analysis, word frequency, word cloud analysis, and Latent Dirichlet Allocation (LDA) topic modeling, this research provides a novel perspective on the preferences and concerns of consumers regarding green consumption. The findings reveal that while there is a predominantly positive sentiment towards green products, the importance of various attributes-including eco-friendliness, quality, price, and functionality-varies significantly across different product categories. The study also identifies specific green and non-green attributes that influence consumer evaluations and discusses the comparative impact of these attributes on shaping positive and negative sentiments. The implications of this study underscore the need for targeted strategies that align with consumer values and preferences revealed through social media analytics, contributing to a more sustainable global market for green products.