Sustainable Consumption in Consumer Behavior in the Time of COVID-19: Topic Modeling on Twitter Data Using LDA
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Cited by:
- Maria Francesca Renzi & Veronica Ungaro & Laura Di Pietro & Roberta Guglielmetti Mugion & Maria Giovina Pasca, 2022. "Agenda 2030 and COVID-19: A Young Consumer’s Perception of Sustainable Consumption," Sustainability, MDPI, vol. 14(23), pages 1-20, November.
- Barbara Zanetti & Milena Verrascina & Francesco Licciardo & Giuseppe Gargano, 2022. "Agritourism and Farms Diversification in Italy: What Have We Learnt from COVID-19?," Land, MDPI, vol. 11(8), pages 1-21, August.
- Martin Zajac & Jiří Horák & Joaquín Osorio-Arjona & Pavel Kukuliač & James Haworth, 2022. "Public Transport Tweets in London, Madrid and Prague in the COVID-19 Period—Temporal and Spatial Differences in Activity Topics," Sustainability, MDPI, vol. 14(24), pages 1-25, December.
- Čiarnienė Ramunė & Vienažindienė Milita & Adamonienė Rūta, 2023. "Teleworking and sustainable behaviour in the context of COVID-19: the case of Lithuania," Engineering Management in Production and Services, Sciendo, vol. 15(1), pages 1-11, March.
- Eleonora Annunziata & Tommaso Pucci & Jacopo Cammeo & Lorenzo Zanni & Marco Frey, 2023. "The mediating role of exogenous shocks in green purchase intention: evidence from italian fashion industry in the Covid-19 era," Italian Journal of Marketing, Springer, vol. 2023(1), pages 59-79, March.
- Leslier Valenzuela-Fernández & Manuel Escobar-Farfán & Mauricio Guerra-Velásquez & Elizabeth Emperatriz García-Salirrosas, 2023. "COVID-19 Effects on Environmentally Responsible Behavior: A Social Impact Perspective from Latin American Countries," IJERPH, MDPI, vol. 20(4), pages 1-21, February.
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Keywords
sustainable consumption; consumer behavior; COVID-19; coronavirus; Twitter; Latent Dirichlet Allocation (LDA); machine learning; semantic analysis; semantic network analysis; sentiment analysis;All these keywords.
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