A Comprehensive Text Mining Application to Understand Social Media's Impact on Consumer Perception of Green Consumption

Abstract

This study proposes a comprehensive deep learning algorithm to understand how social media influences consumers' perceptions of green consumption. The COVID-19 pandemic has prompted society to pay more attention to the interactions between humans and nature. Promoting green consumption is essential to achieve sustainable development goals, necessitating the ability to understand and reshape the public's perception of sustainability. Previous research has used behavioral models and surveys to study green consumption, but they often overlook the perspective of social media. This study employs deep learning algorithms to analyze text and video content on social media to gain insights into customer behaviors and preferences. Data from Twitter and YouTube was collected to develop deep learning algorithms for text classification. In conclusion, this study uses text mining applications to analyze text and video content on social media, aiming to understand how it affects consumers' perceptions of green consumption. The findings provide significant insights into the influence of social media on consumer behaviors and preferences.

Keywords

• text mining
• social media
• sustainability
• green consumption

Sosyal Medyanın Tüketicilerin Yeşil Tüketim Algısı Üzerindeki Etkisini Anlamak için Kapsamlı bir Metin Madenciliği Uygulaması

Abstract

Bu çalışma, sosyal medyanın tüketicilerin yeşil tüketim algılarını nasıl etkilediğini anlamak için kapsamlı bir metin madenciliği uygulaması gerçekleştirmektedir. COVID-19 salgını, toplumun insan ve doğanın nasıl etkileşime girdiğine daha fazla dikkat etmesine neden olmuştur. Yeşil tüketiciliği teşvik etmek, sürdürülebilir kalkınma hedeflerine ulaşmak için gereklidir; bu da kamuoyunun sürdürülebilirlik algısını anlama ve değiştirme becerisini gerektirir. Önceki araştırmalar, yeşil tüketimi incelemek için davranışsal modeller ve anketler kullanmıştır, ancak bunlar genellikle sosyal medyanın bakış açısını göz ardı etmiştir. Bu çalışma, müşteri davranışları ve tercihleri hakkında içgörüler elde etmek için sosyal medyadaki metin ve video içeriğini analiz etmek için metin madenciliği algoritmaları kullanmaktadır. Bu çalışmada Twitter ve YouTube'dan veri toplanarak metin sınıflandırma için metin madenciliği algoritmaları uygulanmıştır. Sonuç olarak bu çalışma, sosyal medyada yer alan metin ve video içeriklerini analiz ederek tüketicilerin yeşil tüketim algılarını nasıl etkilediğini anlamak amacıyla metin madenciliği uygulamaları kullanmaktadır. Elde edilen bulgular, sosyal medyanın tüketici davranışları ve tercihleri üzerindeki etkisine ilişkin önemli içgörüler sunmaktadır.

Keywords

• metin madenciliği
• sosyal medya
• süreklilik
• yeşil tüketim

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