Araştırma Makalesi
BibTex RIS Kaynak Göster

Yenilenebilir Enerji Türleri Üzerine Bir Sosyal Medya Duygu Analizi

Yıl 2024, Cilt: 34 Sayı: 1, 319 - 334, 26.01.2024
https://doi.org/10.18069/firatsbed.1403552

Öz

Bu çalışma, Facebook, Instagram, Quora ve Reddit gibi sosyal medya platformlarından elde edilen verilerle hidro, güneş, rüzgâr ve nükleer gibi çeşitli enerji kaynakları hakkındaki halk görüşlerinin duygu analizini gerçekleştirmektedir. 3,269 bahsetme verisi ile etkileşimler, paylaşımlar ve beğeniler incelenerek bu enerji formlarıyla ilgili güncel tartışmalara kapsamlı bir bakış sunulmaktadır. Yöntem, duygu analizini nicel verilere dayandırarak altta yatan temaları ortaya çıkarmak için nitel içerik incelemesiyle birleştirilmektedir. Sonuçlar genellikle “temiz,” “sürdürülebilir” ve “verimli” olarak tanımlanan yenilenebilir enerjiye, özellikle hidro ve güneş enerjisine karşı güçlü bir olumlu duygu ortaya koymaktadır. Hidro enerjisi, çevresel etkisinin minimum olduğu algısı nedeniyle yüksek bir itibara sahiptir; güneş enerjisi ise iklim değişikliği ile mücadele ve teknolojik ilerlemeler için övgü almaktadır. Rüzgâr enerjisi, görsel ve ses kirliliği endişeleri ve potansiyel vahşi yaşam etkileri nedeniyle eleştirilirken nükleer enerji güvenlik ve atık yönetimi sorunları nedeniyle olumsuz duygular uyandırmaktadır. Bu sonuçlar, yenilenebilir enerji endüstrisi içinde etkili pazarlama stratejileri oluşturmak için önemli sonuçlar sunmaktadır.

Kaynakça

  • Ahmad, A., Rashid, M., Omar, N. A., & Alam, S. S. (2014). Perceptions on Renewable Energy Use in Malaysia: Mediating Role of Attitude. Journal Pengurusan, 41, 123–131.
  • Alqaryouti, O., Siyam, N., Abdel Monem, A., & Shaalan, K. (2020). Aspect-Based Sentiment Analysis using Smart Government Review Data. Applied Computing and Informatics, DOI/10.1016/j.aci.2019.11.003.
  • Al-Shabi, M. (2020). Evaluating the Performance of the Most Important Lexicons Used for Sentiment Analysis and Opinions. Mining. 20, 1.
  • Alshamsi, A., Bayari, R., & Salloum, S. (2020). Sentiment Analysis in English Texts. Advances in Science, Technology and Engineering Systems Journal, 5, (6), 1683-1689.
  • Barone, G., Buonomano, A., Forzano, C., Giuzio, G. F., & Palombo, A. (2021). Increasing Renewable Energy Penetration and Energy Independence of Island Communities: A Novel Dynamic Simulation Approach for Energy, Economic, and Environmental Analysis, and Optimization. Journal of Cleaner Production, 311, 127558, https://doi.org/10.1016/j.jclepro.2021.127558.
  • Bento, N., & Fontes, M. (2019). Emergence of Floating Offshore Wind Energy: Technology and Industry. Renewable and Sustainable Energy Reviews, 99, 66–82.
  • Bilgili, F., Lorente, D. B., Kuşkaya, S., Ünlü, F., Gençoğlu, P., & Rosha, P. (2021). The Role of Hydropower Energy in the Level of CO2 Emissions: An Application of Continuous Wavelet Transform. Renewable Energy, 178, 283–294.
  • Brandmentions. (n.d.). BrandMentions | Upgrade the way You Monitor Your Brand Competitors. https://brandmentions.com/
  • Čábelková, I., Strielkowski, W., Firsova, I., & Korovushkina, M. (2020). Public Acceptance of Renewable Energy Sources: A Case Study from the Czech Republic. Energies, 13, (7), DOI/10.3390/en13071742.
  • Caglar, A. E. (2023). Can Nuclear Energy Technology Budgets Pave the Way for a Transition Toward Low-Carbon Economy: Insights from the United Kingdom. Sustainable Development, 31, (1), 198–210.
  • Chen, X. H., Tee, K., Elnahass, M., & Ahmed, R. (2023). Assessing the Environmental Impacts of Renewable Energy Sources: A Case Study on Air Pollution and Carbon Emissions in China. Journal of Environmental Management, 345, 118525, DOI/10.1016/j.jenvman.2023.118525.
  • Chien, F., Ajaz, T., Andlib, Z., Chau, K. Y., Ahmad, P., & Sharif, A. (2021). The Role of Technology Innovation, Renewable Energy, and Globalization in Reducing Environmental Degradation in Pakistan: A Step towards a Sustainable Environment. Renewable Energy, 177, 308–317.
  • Ghalandari, M., Maleki, A., Haghighi, A., Safdari Shadloo, M., Alhuyi Nazari, M., & Tlili, I. (2020). Applications of Nanofluids Containing Carbon Nanotubes in Solar Energy Systems: A Review. Journal of Molecular Liquids, 313, 113476, DOI/10.1016/j.molliq.2020.113476.
  • Haldar, A., & Sethi, N. (2022). Environmental Effects of Information and Communication Technology—Exploring the Roles of Renewable Energy, Innovation, Trade and Financial Development. Renewable and Sustainable Energy Reviews, 153, 111754, DOI/10.1016/j.rser.2021.111754.
  • Ho, S. S., Leong, A. D., Looi, J., Chen, L., Pang, N., & Tandoc, E. (2019). Science Literacy or Value Predisposition? A Meta-Analysis of Factors Predicting Public Perceptions of Benefits, Risks, and Acceptance of Nuclear Energy. Environmental Communication, 13, (4), 457–471.
  • Ibar-Alonso, R., Quiroga-García, R., & Arenas-Parra, M. (2022). Opinion Mining of Green Energy Sentiment: A Russia-Ukraine Conflict Analysis. Mathematics, 10, (14), DOI/10.3390/math10142532.
  • Isnain, A. R., Supriyanto, J., & Kharisma, M. P. (2021). Implementation of K-Nearest Neighbor (K-NN) Algorithm for Public Sentiment Analysis of Online Learning. IJCCS (Indonesian Journal of Computing and Cybernetics Systems), 15, (2), 121-130.
  • Jain, A., & Jain, V. (2019). Sentiment classification of Twitter Data Belonging to Renewable Energy using Machine Learning. Journal of Information and Optimization Sciences, 40, (2), 521–533.
  • Karaeva, A., Magaril, E., Torretta, V., Viotti, P., & Rada, E. C. (2022). Public Attitude towards Nuclear and Renewable Energy as a Factor of Their Development in a Circular Economy Frame: Two Case Studies. Sustainability, 14, (3), DOI/10.3390/su14031283.
  • Kaygusuz, K. (2001). Renewable Energy: Power for a Sustainable Future. Energy Exploration & Exploitation, 19, (6), 603–626.
  • Kim, S. Y., Ganesan, K., Dickens, P., & Panda, S. (2021). Public Sentiment toward Solar Energy—Opinion Mining of Twitter Using a Transformer-Based Language Model. Sustainability, 13, (5), DOI/10.3390/su13052673
  • Kuriqi, A., Pinheiro, A. N., Sordo-Ward, A., Bejarano, M. D., & Garrote, L. (2021). Ecological Impacts of Run-of-River Hydropower Plants—Current Status and Future Prospects on the Brink of Energy Transition. Renewable and Sustainable Energy Reviews, 142, 110833, DOI/10.1016/j.rser.2021.110833.
  • Li, G., Li, M., Taylor, R., Hao, Y., Besagni, G., & Markides, C. N. (2022). Solar Energy Utilization: Current Status and Roll-Out Potential. Applied Thermal Engineering, 209, 118285, DOI/10.1016/j.applthermaleng.2022.118285.
  • Liang, Y., Ji, X., Wu, C., He, J., & Qin, Z. (2020). Estimation of the Influences of Air Density on Wind Energy Assessment: A Case Study from China. Energy Conversion and Management, 224, 113371, DOI/10.1016/j.enconman.2020.113371.
  • Lin, H.-C. K., Wang, T.-H., Lin, G.-C., Cheng, S.-C., Chen, H.-R., & Huang, Y.-M. (2020). Applying Sentiment Analysis to Classify Consumer Comments Concerning Marketing 4Cs Aspects Automatically. Applied Soft Computing, 97, 106755, DOI/10.1016/j.asoc.2020.106755.
  • Liu, B. (2022). Sentiment Analysis and Opinion Mining. Springer Nature, 1-21.
  • Lund, J. W., & Toth, A. N. (2021). Direct Utilization of Geothermal Energy 2020 Worldwide Review. Geothermics, 90, 101915, DOI/10.1016/j.geothermics.2020.101915.
  • M, A. J., & I, E. S. (2022). Role of Educational Data Mining in Student Learning Processes with Sentiment Analysis: A Survey. In Research Anthology on Interventions in Student Behavior and Misconduct, (16), 412–427.
  • Mahmood, N., Wang, Z., & Hassan, S. T. (2019). Renewable Energy, Economic Growth, Human Capital, and CO2 Emission: An Empirical Analysis. Environmental Science and Pollution Research, 26, (20), 20619–20630.
  • Mbamalu, M. (2020). Newspaper Coverage of Renewable Energy in Nigeria: Frames, Themes, and Actors. SAGE Open, 10, (2), DOI/10.1177/215824402092619.
  • Melton, C. A., Olusanya, O. A., Ammar, N., & Shaban-Nejad, A. (2021). Public Sentiment Analysis and Topic Modeling Regarding COVID-19 Vaccines on the Reddit Social Media Platform: A Call to Action for Strengthening Vaccine Confidence. Journal of Infection and Public Health, 14, (10), 1505–1512.
  • Mutezo, G., & Mulopo, J. (2021). A Review of Africa’s Transition from Fossil Fuels to Renewable Energy using Circular Economy Principles. Renewable and Sustainable Energy Reviews, 137, 110609, DOI/10.1016/j.rser.2020.110609.
  • Nemes, L., & Kiss, A. (2021). Social Media Sentiment Analysis Based on COVID-19. Journal of Information and Telecommunication, 5, (1), 1–15.
  • Olabi, A. G., & Abdelkareem, M. A. (2022). Renewable Energy and Climate Change. Renewable and Sustainable Energy Reviews, 158, 112111, DOI/10.1016/j.rser.2022.112111.
  • Oliveira, A. M., Beswick, R. R., & Yan, Y. (2021). A Green Hydrogen Economy for a Renewable Energy Society. Current Opinion in Chemical Engineering, 33, 100701, DOI/10.1016/j.coche.2021.100701.
  • Olson-Hazboun, S. K., Krannich, R. S., & Robertson, P. G. (2016). Public Views on Renewable Energy in the Rocky Mountain Region of the United States: Distinct Attitudes, Exposure, and Other Key Predictors of Wind Energy. Energy Research & Social Science, 21, 167–179.
  • Păvăloaia, V.-D., Teodor, E.-M., Fotache, D., & Danileţ, M. (2019). Opinion Mining on Social Media Data: Sentiment Analysis of User Preferences. Sustainability, 11, (16), DOI/10.3390/su11164459
  • Ram, M., Aghahosseini, A., & Breyer, C. (2020). Job Creation during the Global Energy Transition towards a 100% Renewable Power System by 2050. Technological Forecasting and Social Change, 151, 119682, DOI/10.1016/j.techfore.2019.06.008.
  • Razmjoo, A., Gakenia Kaigutha, L., Vaziri Rad, M. A., Marzband, M., Davarpanah, A., & Denai, M. (2021). A Technical Analysis Investigating Energy Sustainability Utilizing Reliable Renewable Energy Sources to Reduce CO2 Emissions in a High Potential Area. Renewable Energy, 164, 46–57.
  • Reboredo, J. C., & Ugolini, A. (2018). The Impact of Twitter Sentiment on Renewable Energy Stocks. Energy Economics, 76, 153–169.
  • Rodrigues dos Santos, E., Michalski, F., & Norris, D. (2021). Understanding Hydropower Impacts on Amazonian Wildlife is Limited by a Lack of Robust Evidence: Results from a Systematic Review. Tropical Conservation Science, 14, DOI/10.1177/19400829211045788.
  • Sharif, A., Meo, M. S., Chowdhury, M. A. F., & Sohag, K. (2021). Role of Solar Energy in Reducing Ecological Footprints: An Empirical Analysis. Journal of Cleaner Production, 292, 126028, DOI/10.1016/j.jclepro.2021.126028.
  • Soong, H.-C., Jalil, N. B. A., Kumar Ayyasamy, R., & Akbar, R. (2019). The Essential of Sentiment Analysis and Opinion Mining in Social Media: Introduction and Survey of the Recent Approaches and Techniques. 2019 IEEE 9th Symposium on Computer Applications & Industrial Electronics (ISCAIE), 272–277.
  • Stappen, L., Baird, A., Schumann, L., & Schuller, B. (2023). The Multimodal Sentiment Analysis in Car Reviews (MuSe-CaR) Dataset: Collection, Insights and Improvements. IEEE Transactions on Affective Computing, 14, (2), 1334–1350.
  • Stigka, E. K., Paravantis, J. A., & Mihalakakou, G. K. (2014). Social Acceptance of Renewable Energy Sources: A Review of Contingent Valuation Applications. Renewable and Sustainable Energy Reviews, 32, 100–106.
  • Teias. (2023). Türkiye Electricity Statistics. Load Dispatch Information System. https://ytbsbilgi.teias.gov.tr/ytbsbilgi/frm_istatistikler.jsf
  • Uddin, W., Ayesha, Zeb, K., Haider, A., Khan, B., Islam, S. ul, Ishfaq, M., Khan, I., Adil, M., & Kim, H. J. (2019). Current and Future Prospects of Small Hydro Power in Pakistan: A Survey. Energy Strategy Reviews, 24, 166–177.
  • Vespa, M., Kortsch, T., Hildebrand, J., Schweizer-Ries, P., & Volkmer, S. A. (2022). Not All Places Are Equal: Using Instagram to Understand Cognitions and Affect towards Renewable Energy Infrastructures. Sustainability, 14, (7), DOI/10.3390/su14074071.
  • Viviescas, C., Lima, L., Diuana, F. A., Vasquez, E., Ludovique, C., Silva, G. N., Huback, V., Magalar, L., Szklo, A., Lucena, A. F. P., Schaeffer, R., & Paredes, J. R. (2019). Contribution of Variable Renewable Energy to Increase Energy Security in Latin America: Complementarity and Climate Change Impacts on Wind and Solar Resources. Renewable and Sustainable Energy Reviews, 113, 109232, DOI/10.1016/j.rser.2019.06.039.
  • Wall, W. P., Khalid, B., Urbański, M., & Kot, M. (2021). Factors Influencing Consumer’s Adoption of Renewable Energy. Energies, 14, (17), DOI/10.3390/en14175420.
  • Wang, G., Sadiq, M., Bashir, T., Jain, V., Ali, S. A., & Shabbir, M. S. (2022). The Dynamic Association between Different Strategies of Renewable Energy Sources and Sustainable Economic Growth under SDGs. Energy Strategy Reviews, 42, 100886, DOI/10.1016/j.esr.2022.100886.
  • Wang, M., Wang, G., Sun, Z., Zhang, Y., & Xu, D. (2019). Review of Renewable Energy-Based Hydrogen Production Processes for Sustainable Energy Innovation. Global Energy Interconnection, 2, (5), 436–443.
  • Wang, S., Wang, J., Lin, S., & Li, J. (2019). Public Perceptions and Acceptance of Nuclear Energy in China: The Role of Public Knowledge, Perceived Benefit, Perceived Risk, and Public Engagement. Energy Policy, 126, 352–360.
  • Zeng, Z., Ziegler, A. D., Searchinger, T., Yang, L., Chen, A., Ju, K., Piao, S., Li, L. Z. X., Ciais, P., Chen, D., Liu, J., Azorin-Molina, C., Chappell, A., Medvigy, D., & Wood, E. F. (2019). A Reversal in Global Terrestrial Stilling and Its Implications for Wind Energy Production. Nature Climate Change, 9, (12), 979-985.

A SOCIAL MEDIA SENTIMENT ANALYSIS ON RENEWABLE ENERGY FORMS

Yıl 2024, Cilt: 34 Sayı: 1, 319 - 334, 26.01.2024
https://doi.org/10.18069/firatsbed.1403552

Öz

This study conducts a sentiment analysis of public opinions on various energy sources, including hydro, solar, wind, and nuclear, using data from social media platforms like Facebook, Instagram, Quora, and Reddit. A dataset of 3,269 mentions and examining interactions, shares, and likes offers an extensive view of the current discourse on these energy forms. The methodology combines quantitative sentiment analysis with qualitative content examination to uncover underlying themes. The findings reveal strong positive sentiment towards renewable energy, mainly hydro and solar power, often described as “clean,” “sustainable,” and “efficient.” Hydro energy is highly regarded due to its minimal environmental impact, while solar energy is praised for combating climate change and technological advancements. Wind energy faces criticism for visual and noise pollution concerns and potential effects on wildlife, while nuclear power generates negative sentiments primarily due to safety and waste management issues. These results have important implications for shaping effective marketing strategies within the renewable energy industry.

Kaynakça

  • Ahmad, A., Rashid, M., Omar, N. A., & Alam, S. S. (2014). Perceptions on Renewable Energy Use in Malaysia: Mediating Role of Attitude. Journal Pengurusan, 41, 123–131.
  • Alqaryouti, O., Siyam, N., Abdel Monem, A., & Shaalan, K. (2020). Aspect-Based Sentiment Analysis using Smart Government Review Data. Applied Computing and Informatics, DOI/10.1016/j.aci.2019.11.003.
  • Al-Shabi, M. (2020). Evaluating the Performance of the Most Important Lexicons Used for Sentiment Analysis and Opinions. Mining. 20, 1.
  • Alshamsi, A., Bayari, R., & Salloum, S. (2020). Sentiment Analysis in English Texts. Advances in Science, Technology and Engineering Systems Journal, 5, (6), 1683-1689.
  • Barone, G., Buonomano, A., Forzano, C., Giuzio, G. F., & Palombo, A. (2021). Increasing Renewable Energy Penetration and Energy Independence of Island Communities: A Novel Dynamic Simulation Approach for Energy, Economic, and Environmental Analysis, and Optimization. Journal of Cleaner Production, 311, 127558, https://doi.org/10.1016/j.jclepro.2021.127558.
  • Bento, N., & Fontes, M. (2019). Emergence of Floating Offshore Wind Energy: Technology and Industry. Renewable and Sustainable Energy Reviews, 99, 66–82.
  • Bilgili, F., Lorente, D. B., Kuşkaya, S., Ünlü, F., Gençoğlu, P., & Rosha, P. (2021). The Role of Hydropower Energy in the Level of CO2 Emissions: An Application of Continuous Wavelet Transform. Renewable Energy, 178, 283–294.
  • Brandmentions. (n.d.). BrandMentions | Upgrade the way You Monitor Your Brand Competitors. https://brandmentions.com/
  • Čábelková, I., Strielkowski, W., Firsova, I., & Korovushkina, M. (2020). Public Acceptance of Renewable Energy Sources: A Case Study from the Czech Republic. Energies, 13, (7), DOI/10.3390/en13071742.
  • Caglar, A. E. (2023). Can Nuclear Energy Technology Budgets Pave the Way for a Transition Toward Low-Carbon Economy: Insights from the United Kingdom. Sustainable Development, 31, (1), 198–210.
  • Chen, X. H., Tee, K., Elnahass, M., & Ahmed, R. (2023). Assessing the Environmental Impacts of Renewable Energy Sources: A Case Study on Air Pollution and Carbon Emissions in China. Journal of Environmental Management, 345, 118525, DOI/10.1016/j.jenvman.2023.118525.
  • Chien, F., Ajaz, T., Andlib, Z., Chau, K. Y., Ahmad, P., & Sharif, A. (2021). The Role of Technology Innovation, Renewable Energy, and Globalization in Reducing Environmental Degradation in Pakistan: A Step towards a Sustainable Environment. Renewable Energy, 177, 308–317.
  • Ghalandari, M., Maleki, A., Haghighi, A., Safdari Shadloo, M., Alhuyi Nazari, M., & Tlili, I. (2020). Applications of Nanofluids Containing Carbon Nanotubes in Solar Energy Systems: A Review. Journal of Molecular Liquids, 313, 113476, DOI/10.1016/j.molliq.2020.113476.
  • Haldar, A., & Sethi, N. (2022). Environmental Effects of Information and Communication Technology—Exploring the Roles of Renewable Energy, Innovation, Trade and Financial Development. Renewable and Sustainable Energy Reviews, 153, 111754, DOI/10.1016/j.rser.2021.111754.
  • Ho, S. S., Leong, A. D., Looi, J., Chen, L., Pang, N., & Tandoc, E. (2019). Science Literacy or Value Predisposition? A Meta-Analysis of Factors Predicting Public Perceptions of Benefits, Risks, and Acceptance of Nuclear Energy. Environmental Communication, 13, (4), 457–471.
  • Ibar-Alonso, R., Quiroga-García, R., & Arenas-Parra, M. (2022). Opinion Mining of Green Energy Sentiment: A Russia-Ukraine Conflict Analysis. Mathematics, 10, (14), DOI/10.3390/math10142532.
  • Isnain, A. R., Supriyanto, J., & Kharisma, M. P. (2021). Implementation of K-Nearest Neighbor (K-NN) Algorithm for Public Sentiment Analysis of Online Learning. IJCCS (Indonesian Journal of Computing and Cybernetics Systems), 15, (2), 121-130.
  • Jain, A., & Jain, V. (2019). Sentiment classification of Twitter Data Belonging to Renewable Energy using Machine Learning. Journal of Information and Optimization Sciences, 40, (2), 521–533.
  • Karaeva, A., Magaril, E., Torretta, V., Viotti, P., & Rada, E. C. (2022). Public Attitude towards Nuclear and Renewable Energy as a Factor of Their Development in a Circular Economy Frame: Two Case Studies. Sustainability, 14, (3), DOI/10.3390/su14031283.
  • Kaygusuz, K. (2001). Renewable Energy: Power for a Sustainable Future. Energy Exploration & Exploitation, 19, (6), 603–626.
  • Kim, S. Y., Ganesan, K., Dickens, P., & Panda, S. (2021). Public Sentiment toward Solar Energy—Opinion Mining of Twitter Using a Transformer-Based Language Model. Sustainability, 13, (5), DOI/10.3390/su13052673
  • Kuriqi, A., Pinheiro, A. N., Sordo-Ward, A., Bejarano, M. D., & Garrote, L. (2021). Ecological Impacts of Run-of-River Hydropower Plants—Current Status and Future Prospects on the Brink of Energy Transition. Renewable and Sustainable Energy Reviews, 142, 110833, DOI/10.1016/j.rser.2021.110833.
  • Li, G., Li, M., Taylor, R., Hao, Y., Besagni, G., & Markides, C. N. (2022). Solar Energy Utilization: Current Status and Roll-Out Potential. Applied Thermal Engineering, 209, 118285, DOI/10.1016/j.applthermaleng.2022.118285.
  • Liang, Y., Ji, X., Wu, C., He, J., & Qin, Z. (2020). Estimation of the Influences of Air Density on Wind Energy Assessment: A Case Study from China. Energy Conversion and Management, 224, 113371, DOI/10.1016/j.enconman.2020.113371.
  • Lin, H.-C. K., Wang, T.-H., Lin, G.-C., Cheng, S.-C., Chen, H.-R., & Huang, Y.-M. (2020). Applying Sentiment Analysis to Classify Consumer Comments Concerning Marketing 4Cs Aspects Automatically. Applied Soft Computing, 97, 106755, DOI/10.1016/j.asoc.2020.106755.
  • Liu, B. (2022). Sentiment Analysis and Opinion Mining. Springer Nature, 1-21.
  • Lund, J. W., & Toth, A. N. (2021). Direct Utilization of Geothermal Energy 2020 Worldwide Review. Geothermics, 90, 101915, DOI/10.1016/j.geothermics.2020.101915.
  • M, A. J., & I, E. S. (2022). Role of Educational Data Mining in Student Learning Processes with Sentiment Analysis: A Survey. In Research Anthology on Interventions in Student Behavior and Misconduct, (16), 412–427.
  • Mahmood, N., Wang, Z., & Hassan, S. T. (2019). Renewable Energy, Economic Growth, Human Capital, and CO2 Emission: An Empirical Analysis. Environmental Science and Pollution Research, 26, (20), 20619–20630.
  • Mbamalu, M. (2020). Newspaper Coverage of Renewable Energy in Nigeria: Frames, Themes, and Actors. SAGE Open, 10, (2), DOI/10.1177/215824402092619.
  • Melton, C. A., Olusanya, O. A., Ammar, N., & Shaban-Nejad, A. (2021). Public Sentiment Analysis and Topic Modeling Regarding COVID-19 Vaccines on the Reddit Social Media Platform: A Call to Action for Strengthening Vaccine Confidence. Journal of Infection and Public Health, 14, (10), 1505–1512.
  • Mutezo, G., & Mulopo, J. (2021). A Review of Africa’s Transition from Fossil Fuels to Renewable Energy using Circular Economy Principles. Renewable and Sustainable Energy Reviews, 137, 110609, DOI/10.1016/j.rser.2020.110609.
  • Nemes, L., & Kiss, A. (2021). Social Media Sentiment Analysis Based on COVID-19. Journal of Information and Telecommunication, 5, (1), 1–15.
  • Olabi, A. G., & Abdelkareem, M. A. (2022). Renewable Energy and Climate Change. Renewable and Sustainable Energy Reviews, 158, 112111, DOI/10.1016/j.rser.2022.112111.
  • Oliveira, A. M., Beswick, R. R., & Yan, Y. (2021). A Green Hydrogen Economy for a Renewable Energy Society. Current Opinion in Chemical Engineering, 33, 100701, DOI/10.1016/j.coche.2021.100701.
  • Olson-Hazboun, S. K., Krannich, R. S., & Robertson, P. G. (2016). Public Views on Renewable Energy in the Rocky Mountain Region of the United States: Distinct Attitudes, Exposure, and Other Key Predictors of Wind Energy. Energy Research & Social Science, 21, 167–179.
  • Păvăloaia, V.-D., Teodor, E.-M., Fotache, D., & Danileţ, M. (2019). Opinion Mining on Social Media Data: Sentiment Analysis of User Preferences. Sustainability, 11, (16), DOI/10.3390/su11164459
  • Ram, M., Aghahosseini, A., & Breyer, C. (2020). Job Creation during the Global Energy Transition towards a 100% Renewable Power System by 2050. Technological Forecasting and Social Change, 151, 119682, DOI/10.1016/j.techfore.2019.06.008.
  • Razmjoo, A., Gakenia Kaigutha, L., Vaziri Rad, M. A., Marzband, M., Davarpanah, A., & Denai, M. (2021). A Technical Analysis Investigating Energy Sustainability Utilizing Reliable Renewable Energy Sources to Reduce CO2 Emissions in a High Potential Area. Renewable Energy, 164, 46–57.
  • Reboredo, J. C., & Ugolini, A. (2018). The Impact of Twitter Sentiment on Renewable Energy Stocks. Energy Economics, 76, 153–169.
  • Rodrigues dos Santos, E., Michalski, F., & Norris, D. (2021). Understanding Hydropower Impacts on Amazonian Wildlife is Limited by a Lack of Robust Evidence: Results from a Systematic Review. Tropical Conservation Science, 14, DOI/10.1177/19400829211045788.
  • Sharif, A., Meo, M. S., Chowdhury, M. A. F., & Sohag, K. (2021). Role of Solar Energy in Reducing Ecological Footprints: An Empirical Analysis. Journal of Cleaner Production, 292, 126028, DOI/10.1016/j.jclepro.2021.126028.
  • Soong, H.-C., Jalil, N. B. A., Kumar Ayyasamy, R., & Akbar, R. (2019). The Essential of Sentiment Analysis and Opinion Mining in Social Media: Introduction and Survey of the Recent Approaches and Techniques. 2019 IEEE 9th Symposium on Computer Applications & Industrial Electronics (ISCAIE), 272–277.
  • Stappen, L., Baird, A., Schumann, L., & Schuller, B. (2023). The Multimodal Sentiment Analysis in Car Reviews (MuSe-CaR) Dataset: Collection, Insights and Improvements. IEEE Transactions on Affective Computing, 14, (2), 1334–1350.
  • Stigka, E. K., Paravantis, J. A., & Mihalakakou, G. K. (2014). Social Acceptance of Renewable Energy Sources: A Review of Contingent Valuation Applications. Renewable and Sustainable Energy Reviews, 32, 100–106.
  • Teias. (2023). Türkiye Electricity Statistics. Load Dispatch Information System. https://ytbsbilgi.teias.gov.tr/ytbsbilgi/frm_istatistikler.jsf
  • Uddin, W., Ayesha, Zeb, K., Haider, A., Khan, B., Islam, S. ul, Ishfaq, M., Khan, I., Adil, M., & Kim, H. J. (2019). Current and Future Prospects of Small Hydro Power in Pakistan: A Survey. Energy Strategy Reviews, 24, 166–177.
  • Vespa, M., Kortsch, T., Hildebrand, J., Schweizer-Ries, P., & Volkmer, S. A. (2022). Not All Places Are Equal: Using Instagram to Understand Cognitions and Affect towards Renewable Energy Infrastructures. Sustainability, 14, (7), DOI/10.3390/su14074071.
  • Viviescas, C., Lima, L., Diuana, F. A., Vasquez, E., Ludovique, C., Silva, G. N., Huback, V., Magalar, L., Szklo, A., Lucena, A. F. P., Schaeffer, R., & Paredes, J. R. (2019). Contribution of Variable Renewable Energy to Increase Energy Security in Latin America: Complementarity and Climate Change Impacts on Wind and Solar Resources. Renewable and Sustainable Energy Reviews, 113, 109232, DOI/10.1016/j.rser.2019.06.039.
  • Wall, W. P., Khalid, B., Urbański, M., & Kot, M. (2021). Factors Influencing Consumer’s Adoption of Renewable Energy. Energies, 14, (17), DOI/10.3390/en14175420.
  • Wang, G., Sadiq, M., Bashir, T., Jain, V., Ali, S. A., & Shabbir, M. S. (2022). The Dynamic Association between Different Strategies of Renewable Energy Sources and Sustainable Economic Growth under SDGs. Energy Strategy Reviews, 42, 100886, DOI/10.1016/j.esr.2022.100886.
  • Wang, M., Wang, G., Sun, Z., Zhang, Y., & Xu, D. (2019). Review of Renewable Energy-Based Hydrogen Production Processes for Sustainable Energy Innovation. Global Energy Interconnection, 2, (5), 436–443.
  • Wang, S., Wang, J., Lin, S., & Li, J. (2019). Public Perceptions and Acceptance of Nuclear Energy in China: The Role of Public Knowledge, Perceived Benefit, Perceived Risk, and Public Engagement. Energy Policy, 126, 352–360.
  • Zeng, Z., Ziegler, A. D., Searchinger, T., Yang, L., Chen, A., Ju, K., Piao, S., Li, L. Z. X., Ciais, P., Chen, D., Liu, J., Azorin-Molina, C., Chappell, A., Medvigy, D., & Wood, E. F. (2019). A Reversal in Global Terrestrial Stilling and Its Implications for Wind Energy Production. Nature Climate Change, 9, (12), 979-985.
Toplam 54 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular Dijital Reklamcılık, Reklam Araştırmaları, Reklam Stratejileri, Reklam-Medya Planlamaları
Bölüm İletişim
Yazarlar

Hafize Nurgül Durmuş Şenyapar 0000-0003-0927-1643

Yayımlanma Tarihi 26 Ocak 2024
Gönderilme Tarihi 11 Aralık 2023
Kabul Tarihi 13 Ocak 2024
Yayımlandığı Sayı Yıl 2024 Cilt: 34 Sayı: 1

Kaynak Göster

APA Durmuş Şenyapar, H. N. (2024). A SOCIAL MEDIA SENTIMENT ANALYSIS ON RENEWABLE ENERGY FORMS. Firat University Journal of Social Sciences, 34(1), 319-334. https://doi.org/10.18069/firatsbed.1403552