Journals / The Eurasia Proceedings of Science Technology Engineering and Mathematics / 2026 / Volume: 23

Embracing Green Choices: Sentiment Analysis of Sustainable Consumption

Ceren Cubukcu-cerasi(GEBZE TECHNICAL UNIVERSITY)
Yavuz Selim Balcıoglu(GEBZE TECHNICAL UNIVERSITY)
Aslı Kılıc(GEBZE TEKNİK ÜNİVERSİTESİ)
Farid Huseynov(GEBZE TECHNICAL UNIVERSITY)
Pages
—
Publication Date
2023-09-30
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

Overall, the study shows how data mining techniques and social networks have the potential to help with the shift to more sustainable growth paths.

📌 3 Key Takeaways

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Objective & Hypothesis:Currently, resource scarcity and climate change are among the main global problems.
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Key Findings & Data:This research aims to explore the sentiment and attitudes towards sustainable consumption on YouTube, a popular online platform with a vast pool of user-generated content.
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Conclusion & Impact:Overall, the study shows how data mining techniques and social networks have the potential to help with the shift to more sustainable growth paths.
🔬Design:Lab & Field Experiment
📍Scope:Comprehensive Sample
⚙️Variables:Sustainability · Green consumption · Sentiment analysis

Abstract

Currently, resource scarcity and climate change are among the main global problems. Governments are actively seeking regenerative solutions so that humans and nature can co-exist in harmony in the face of ecological destruction and resource limitations. One of these solutions is green consumption. Making greener consumption decisions is necessary for society to become sustainable. If sustainable consumption is to be promoted, public perception must shift, and achieving this shift will be simpler if society's shift toward green consumption is understood. This research aims to explore the sentiment and attitudes towards sustainable consumption on YouTube, a popular online platform with a vast pool of user-generated content. We employ a combination of data mining techniques and sentiment analysis to process and analyze a large dataset of YouTube videos and comments related to sustainable consumption topics. The data collection includes videos from various categories, such as reviews of eco-friendly products, vlogs of sustainable living, and informative content on environmentally responsible practices. The study focusses on understanding user engagement, sentiment polarity, and the factors influencing positive or negative attitudes toward sustainable consumption. In this way, the attitude of society toward green consumption and the role of social networks in public opinion can be understood. Overall, the study shows how data mining techniques and social networks have the potential to help with the shift to more sustainable growth paths.

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Cite This Article

Cubukcu-cerasi, C., Balcıoglu, Y. S., Kılıc, A., Huseynov, F. (2023). Embracing Green Choices: Sentiment Analysis of Sustainable Consumption. The Eurasia Proceedings of Science Technology Engineering and Mathematics, Volume: 23. https://doi.org/10.55549/epstem.1365803

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References (5)

  1. Bedard, S. A. N., & Tolmie, C. R. (2018). Millennials' green consumption behaviour: Exploring the role of social media. Corporate Social Responsibility and Environmental Management, 25(6), 1388-1396.
  2. Biswas, A. (2016). Impact of social media usage factors on green consumption behavior based on technology acceptance model. Journal of Advanced Management Science, 4(2), 92-97.
  3. Bocken, N. (2017). Business-led sustainable consumption initiatives: Impacts and lessons learned. Journal of Management Development, 36(1), 81-96.
  4. Charter, M., Gray, C., Clark, T., & Woolman, T. (2017). The role of business in realising sustainable consumption and production. In System Innovation for Sustainability 1 (pp. 56-79). Routledge.
  5. Biswas, A. (2016). Impact of social media usage factors on green consumption behavior based on technology acceptance model. Journal of Advanced Management Science, 4(2), 92-97.