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Are Investors Interested in Sustainability? A Latent Semantic Analysis of Data from Social Media

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  • Riccardo Ricciardi

    (University of Brescia)

  • Chiara Avanzi

    (University of Brescia)

  • Marica Manisera

    (University of Brescia)

Abstract

This study examines the level of investor interest in sustainability topics as reflected in discussions on StockTwits, a microblogging platform dedicated to sharing content on financial markets. By analyzing investor posts using a set of keywords aligned with the economic, environmental, and social dimensions of sustainability, this study applies word frequency analysis and Latent Semantic Analysis (LSA), to assess the representation and trends of sustainability discourse from 2010 to 2021. The word frequency analysis indicates a gradual but accelerating rise in the use of sustainability-related terms. Through LSA, sustainability topics are analyzed for their relative importance within the corpus, allowing for an assessment of their prominence compared to other concepts. This technique facilitates the identification of specific sub-aspects of sustainability that are most represented in discussions. The findings indicate that sustainability topics currently hold a limited presence compared to the overall range of concepts discussed on StockTwits. However, when sustainability is addressed, it is primarily linked to themes of clean energy and renewable resources in particular, and more broadly to environmental sustainability, with economic and social sustainability aspects receiving comparatively less attention. The study contributes to the literature on social media as a lens for investors’ interests, particularly regarding sustainability awareness and its implications for market trends.

Suggested Citation

  • Riccardo Ricciardi & Chiara Avanzi & Marica Manisera, 2025. "Are Investors Interested in Sustainability? A Latent Semantic Analysis of Data from Social Media," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 180(2), pages 865-885, November.
    • Handle: RePEc:spr:soinre:v:180:y:2025:i:2:d:10.1007_s11205-025-03693-9
    DOI: 10.1007/s11205-025-03693-9
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