Understanding #WorldEnvironmentDay User Opinions in Twitter: A Topic-Based Sentiment Analysis Approach
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- Shu Ishida & Takanori Matsui & Chihiro Haga & Keiko Hori & Shizuka Hashimoto & Osamu Saito, 2023. "Twitter Mining for Detecting Interest Trends on Biodiversity: Messages from Seven Language Communities," Sustainability, MDPI, vol. 15(17), pages 1-29, August.
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- Stefano Bruzzese & Wasim Ahmed & Simone Blanc & Filippo Brun, 2022. "Ecosystem Services: A Social and Semantic Network Analysis of Public Opinion on Twitter," IJERPH, MDPI, vol. 19(22), pages 1-15, November.
- Seungil Yum, 2022. "Social networks and spatial-temporal analyses for winter storm Jupiter in the US in 2017," Quality & Quantity: International Journal of Methodology, Springer, vol. 56(4), pages 2091-2105, August.
- Eva L. Jenkins & Dickson Lukose & Linda Brennan & Annika Molenaar & Tracy A. McCaffrey, 2023. "Exploring Food Waste Conversations on Social Media: A Sentiment, Emotion, and Topic Analysis of Twitter Data," Sustainability, MDPI, vol. 15(18), pages 1-26, September.
- Araceli Galiano-Coronil & Manuela Ortega-Gil & Belén Macías-Varela & Rafael Ravina-Ripoll, 2023. "An approach for analysing and segmenting messages about the SDGs on Twitter from the perspective of social marketing," International Review on Public and Nonprofit Marketing, Springer;International Association of Public and Non-Profit Marketing, vol. 20(3), pages 635-658, September.
- Enara Zarrabeitia-Bilbao & Rosa-María Rio-Belver & Izaskun Alvarez-Meaza & Itziar Martínez de Alegría-Mancisidor, 2022. "World Environment Day: Understanding Environmental Programs Impact on Society Using Twitter Data Mining," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 164(1), pages 263-284, November.
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Keywords
#WorldEnviromentDay; sentiment analysis; Twitter; Python; Sustainable Development Goals; machine learning; Nvivo; textual analysis;All these keywords.
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