A Sentiment Analysis to Understand the Role of Twitter Towards Sustainable Consumption

Abstract

This study conducts a sentiment analysis to understand the role of Twitter in promoting sustainability and green consumption. By using text mining and deep learning techniques on structural and semi-structured data from Twitter, the study aims to measure public attitudes towards green consumption and identify key points of attitude change. To carry out the sentiment analysis, the researchers first identified relevant keywords associated with green consumption and collected tweets about these keywords using a social network analyzer. The collected data was then preprocessed and analyzed using a multimodal deep learning algorithm. The results of the analysis were then used to understand the public’s perspective on green consumption and identify factors that influence consumer behavior. The findings of the study suggest that social media can be a valuable source of information for understanding and influencing public attitudes towards sustainability and green consumption. Overall, the research highlights the potential of using deep learning techniques and social media data to support the transition to more sustainable development pathways.