A content analysis: analyzing topics of conversation under the #sustainability hashtag on Twitter

Abstract

Abstract This study aimed to identify and understand the major topics of discussion under the #sustainability hashtag on Twitter (now known as “X”) and understand user engagement. The sharp increase in social media usage combined with a rise in climate anomalies in recent years makes the area of sustainability with respect to social media a critical topic. Python was used to gather Twitter posts between January 1, 2023, and March 1, 2023. User engagement metrics were analyzed using a variety of statistical analysis methods, including keyword-frequency analysis and Latent Dirichlet Allocation (LDA), which were used to identify significant topics of discussion under the #sustainability hashtag. Additionally, histograms and scatter plots were used to visualize user engagement. LDA analysis was conducted with 7 topics after trials were run with various topics and results were analyzed to determine which number of topics best fit the dataset. The frequency analysis provided a basic overview of the discourse surrounding #sustainability with the topics of technology, business and industry, environmental awareness, and discussion of the future. The LDA model provided a more comprehensive view, including additional topics such as Environmental, Social, and Governance (ESG) and infrastructure, investing, collaboration, and education. These findings have implications for researchers, businesses, organizations, and politicians seeking to align their strategies and actions with the major topics surrounding sustainability on Twitter to have a greater impact on their audience. Researchers can use the results of this study to guide further research on the topic or contextualize their study with existing literature within the field of sustainability.