Research Article
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Year 2023, Volume: 7 Issue: Special Issue - Emerging Technologies and Technology Integration in Education, 1 - 21, 30.04.2023
https://doi.org/10.54535/rep.1206924

Abstract

References

  • Akkas-Baysal, E., Ocak, G., & Ocak, I. (2020). Parents’ view of preschool children on eba and other distance education activities during the covid-19 outbreak. Journal of International Social Science Education, 6(2), 185-214. https://doi.org/10.47615/issej.835211
  • Alan, U. (2021). Distance education during the COVID-19 pandemic in Turkey: Identifying the needs of early childhood educators. Early Childhood Education Journal, 49, 987-994. https://doi.org/10.1007/s10643-021-01197-y
  • Aristovnik, A., Keržič, D., Ravšelj, D., Tomaževič, N., & Umek, L. (2020). Impacts of the COVID-19 pandemic on life of higher education students: A global perspective. Sustainability, 12(20), 8438. https://doi.org/10.3390/su12208438
  • Armitage, R., & Nellums, L. B. (2020). Considering inequalities in the school closure response to COVID-19. The Lancet, 8, e644. https://doi.org/10.1016/S2214-109X(20)30116-9
  • Ayda, K. N., Bastas, M., Altinay, F., Altinay, Z., & Dagli, G. (2020). Distance Education for Students with Special Needs in Primary Schools in the Period of CoVid-19 Epidemic. Propósitos y Representaciones, 8(3), e587. http://dx.doi.org/10.20511/pyr2020.v8n3.587
  • Barkur, G., Vibha, Kamath, & G. B. (2020). Sentiment analysis of nationwide lockdown due to COVID 19 outbreak: Evidence from India. Asian Journal of Psychiatry, 51, 1-2. https://doi.org/10.1016/j.ajp.2020.102089
  • Blei, D. M., Ng, A. Y., & Jordan, M. I. (2003). Latent dirichlet allocation. The Journal of Machine Learning Research, 3, 993-1022.
  • Bird, S., Klein, E., & Loper, E. (2009). Natural language processing with Python: Analyzing text with the natural language toolkit. O'Reilly Media, Inc.
  • Bostan, S., Erdem, R., Ozturk, Y. E., Kilic, T., & Yilmaz, A. (2020). The effect of COVID-19 pandemic on the Turkish society. Electronic Journal of General Medicine, 17(6), 1-8. https://doi.org/10.29333/ejgm/7944
  • Bozkurt, A., Jung, I., Xiao, J., Vladimirschi, V., Schuwer, R., Egorov, G., ... Paskevicius, M. (2020). A global outlook to the interruption of education due to COVID-19 pandemic: Navigating in a time of uncertainty and crisis. Asian Journal of Distance Education, 15(1), 1-126. https://doi.org/10.5281/zenodo.3878572
  • Calderón-Garrido, D., & Gustems-Carnicer, J. (2020). Adaptations of music education in primary and secondary school due to COVID-19: the experience in Spain. Music Education Research, 1-12. https://doi.org/10.1080/14613808.2021.1902488
  • Campos, M. M., & Vieira, L. F. (2020). COVID-19 and early childhood in Brazil: Impacts on children’s well-being, education and care. European Early Childhood Education Research Journal, 1-16. https://doi.org/10.1080/1350293X.2021.1872671
  • Chuang, J., Manning, C. D., & Heer, J. (2012). Termite: Visualization techniques for assessing textual topic models. Proceedings of the international working conference on advanced visual interfaces, 74-77. http://vis.stanford.edu/files/2012-Termite-AVI.pdf
  • Cicha, K., Rizun, M., Rutecka, P., & Strzelecki, A. (2021). COVID-19 and higher education: First-year students’ expectations towards distance learning. Sustainability, 13, 1889. https://doi.org/10.3390/su13041889
  • Crannell, W. C., Clark, E., Jones, C., James, T. A., & Moore, J. (2016). A pattern-matched Twitter analysis of US cancer-patient sentiments. Journal of Surgical Research, 206(2), 536-542. https://doi.org/10.1016/j.jss.2016.06.050
  • Deerwester, S., Dumais, S. T., Furnas, G. W., Landauer, T. K., & Harshman, R. (1990). Indexing by latent semantic analysis. Journal of the American Society for Information Science, 41(6), 391-407.
  • Ding, K., Li, J., & Zhang, Y. (2020). Hashtags, Emotions, and Comments: A large-scale dataset to understand fine-grained social emotions to online topics. Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing, 1376–1382. http://dx.doi.org/10.18653/v1/2020.emnlp-main.106
  • Dogan, S., & Kocak, E. (2020). A study on distance learning activities in the context of the EBA system. Journal of Economics and Social Research, 7(14), 110-124. http://www.ekosad.net/FileUpload/ep939088/File/42_soner_dogan.pdf
  • Duran, M. (2021). The effects of COVID-19 pandemic on preschool education. International Journal of Educational Methodology, 7(2), 249-260. https://doi.org/10.12973/ijem.7.2.249
  • Eutsler, L., Antonenko, P. D., & Mitchell, C. (2020). Initial response to COVID-19: A mixed-methods analysis of media and school communications to identify pedagogical implications for remote teaching. Interactive Technology and Smart Education, 18(2), 227-245. https://doi.org/10.1108/ITSE-08-2020-0159
  • Ewing, L-A., & Cooper, H. B. (2021). Technology-enabled remote learning during COVID-19: Perspectives of Australian teachers, students, and parents. Technology, Pedagogy, and Education, 30(1) 41-57. https://doi.org/10.1080/1475939X.2020.1868562
  • Foo, C., Cheung, B., & Chu, K. (2021). A comparative study regarding distance learning and the conventional face-to-face approach conducted problem-based learning tutorial during the COVID-19 pandemic. BMC Medical Education, 21(141), 1-6. https://doi.org/10.1186/s12909-021-02575-1
  • Goksoy, S. (2017). Pre-school educational process of Turkey. Open Journal of Social Sciences, 5, 73-83. https://doi.org/10.4236/jss.2017.53008
  • Gonzales, A. L., Calarco, J. M., & Lynch, T. (2020). Technology problems and student achievement gaps: A validation and extension of the technology maintenance construct. Communication Research, 47(5), 750-770. https://doi.org/10.1177%2F0093650218796366
  • Haider, M., & Yasmin, A. (2021). A gender base analysis of learners’ perceptions of online education in the context of Covid-19. Pakistan Journal of Gender Studies, 21(1), 33-62. https://doi.org/10.46568/pjgs.v21i1.514
  • Hodges, C., Moore, S., Lockee, B., Trust, T., & Bond, A. (2020, March 27). The difference between emergency remote teaching and online learning. EDUCAUSE Review. https://er.educause.edu/articles/2020/3/the-difference-between-emergency-remote-teaching-and-online-learning
  • Hofmann, T. (1999). Probabilistic latent semantic indexing. Proceedings of the 22nd annual international ACM SIGIR conference on research and development in information retrieval, 50-57. https://doi.org/10.1145/312624.312649
  • Inan, H. Z. (2020). Restructuring early childhood education during the COVID-19 pandemic. Milli Egitim, 49(1), 831-849. https://doi.org/10.37669/milliegitim.754307
  • Johnson, N., Veletsianos, G., & Seaman, J. (2020). U.S. faculty and administrators' experiences and approaches in the early weeks of the COVID-19 pandemic. Online Learning, 24(2), 6-21. https://doi.org/10.24059/olj.v24i2.2285
  • Khlaif, Z. N., Salha, S., & Kouraichi, B. (2021). Emergency remote learning during COVID-19 crisis: Students’ engagement. Education and Information Technologies, 26, 7033-7055. https://doi.org/10.1007/s10639-021-10566-4
  • Konca, A. S., & Cakir, T. (2021). Investigation of parents’ views on distance education of children’s transition from preschool education to primary school during the pandemic process. Journal of Education for Life, 35(2), 52-545. https://doi.org/10.33308/26674874.2021352307
  • Lesh, J. J. (2020). Navigating two pandemics: Racism/inequity and COVID-29: Thoughts from a former special education teacher. Teaching Exceptional Children, 53(1), 7-9.
  • Lytridis, C., Bazinas, C., Sidiropoulos, G., Papakostas, G. A., Kaburlasos, V. G., Nikopoulou, V.-A., Holeva, V., & Evangeliou, A. (2020). Distance special education delivery by social robots. Electronics, 9(6), 1034. https://doi.org/10.3390/electronics9061034
  • McFayden, T. C., Breaux, R., Bertollo, J. R., Cummings, K., & Ollendick, T. H. (2021). COVID-19 remote learning experiences of youth with neurodevelopmental disorders in rural appalachia. Journal of Rural Mental Health, 45(2), 72-85. https://doi.org/10.1037/rmh0000171
  • Means, B., Neisler, J., & Langer Research Associates. (2020). Suddenly online: A national survey of undergraduates during the COVID-19 pandemic. Digital Promise. https://digitalpromise.org/wp-content /uploads/ 2020/ 07/ ELE_CoBrand_DP_FINAL_3.pdf
  • Mungen, A. A., Aygun, I., & Kaya, M. (2020). Finding the relationship between news and social media users’ emotions in the COVID-19 process. Sakarya University Journal of Computer and Information Sciences, 3(3), 250-263. http://saucis.sakarya.edu.tr/en/download/article-file/1413664
  • Nazli, A. K., Kocaomer, C., Besbudak, M., & Koker, N. E. (2021). Understanding the initial reactions of Turkish Twitter users during the COVID-19 pandemic. The Turkish Online Journal of Design, Art and Communication, 11(1), 20-41. http://www.tojdac.org/tojdac/VOLUME11-ISSUE1_files/tojdac_v011i1102.pdf
  • Ozturk, N., & Ayvaz, S., (2018). Sentiment analysis on Twitter: A text mining approach to the Syrian refugee crisis. Telematics and Informatics, 35(1), 136-147. https://doi.org/10.1016/j.tele.2017.10.006
  • Parmigiani, D., Benigno, V., Giusto, M., Silvaggio, C., & Sperandio, S. (2020). E-inclusion: online special education in Italy during the Covid-19 pandemic. Technology, Pedagogy and Education, 30(1), 111-124. https://doi.org/10.1080/1475939X.2020.1856714
  • Pregowska, A., Masztalerz, K., Garlinska, M., & Osial, M. (2021). A worldwide journey through distance education-from the post office to virtual, augmented and mixed realities, and education during the COVID-19 pandemic. Education Sciences, 11(3), 118. https://doi.org/10.3390/educsci11030118
  • Psacharopoulos, G., Collis, V., Patrinos, H. A., & Vegas, E. (2020). Lost Wages: The COVID-19 Cost of School Closures. World Bank Policy Research Working Paper, 9246. World Bank. https://openknowledge.worldbank.org/handle/10986/34387
  • Rehurek, R., & Sojka, P. (2010). Software framework for topic modelling with large corpora. Proceedings of the LREC 2010 workshop on new challenges for NLP frameworks, 46-50. https://www.researchgate.net/publication/255820377_Software_Framework_for_Topic_Modelling_with_Large_Corpora
  • Robin, Dhiman, N., & Chauhan, A. (2020). A study on establishing the online teaching-learning for higher education during COVID-19 in India. Journal of Critical Reviews, 7(13), 4066-4075. https://www.bibliomed.org/mnsfulltext/197/197-1601619916.pdf?1639937284
  • Roy, S., & Ghosh, P. (2021). A comparative study on distancing, mask and vaccine adoption rates from global Twitter trends. Healthcare, 9, 488. https://doi.org/10.3390/healthcare9050488
  • Sahin, T., Gumus, H., & Gencoglu, C. (2021). Analysis of tweets related with physical activity during COVID-19 outbreak. Journal of Basic and Clinical Health Sciences, 1, 42-48. https://doi.org/10.30621/jbachs.869506
  • Sariman, G., & Mutaf, E. (2020). Sentiment analysis of Twitter messages in COVID-19 process. Eurasia Journal of Mathematics, Engineering, Natural & Medical Sciences, 7(10), 137-148. http://dx.doi.org/10.38065/euroasiaorg.149
  • Sider, S. R. (2020). School principles and students with special education needs in a pandemic: Emerging insights from Ontario, Canada. ISEA, 48(2), 78-84. https://www.thecommonwealth-educationhub.net/wp-content/uploads/2020/09/ISEA-2020-482.pdf#page=84
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Sentiments towards Emergency Remote Teaching on Twitter: A Longitudinal Comparative Sentiment Analysis

Year 2023, Volume: 7 Issue: Special Issue - Emerging Technologies and Technology Integration in Education, 1 - 21, 30.04.2023
https://doi.org/10.54535/rep.1206924

Abstract

This longitudinal and comparative study investigated people’s sentiments toward emergency remote teaching in tweets posted in two different languages from January 10 to August 16 2021 when mass vaccinations started and continued. The results indicated that English tweets (a) included more positive sentiments towards emergency remote teaching; (b) were more supportive and motivating; and (c) focused on topics related to education, online education, and English as a second or foreign language. However, Turkish tweets (a) included more similar amounts of neutral and positive sentiments; (b) involved politics and government-related content; and (c) touched on topics related to preschool education, ministry of national education and the e-school system used during the pandemic. Lastly, compared to positive and neutral sentiments, there were fewer negative sentiments in tweets in both languages suggesting that people got used to emergency remote teaching over time. In other words, despite any ongoing issues, people’s reactions to emergency remote teaching on Twitter improved and became either more neutral or positive in a year or so, which implies that increasing optimism due to vaccinations during sudden health crises may calibrate people’s sentiments towards compulsory solutions such as emergency remote teaching.

References

  • Akkas-Baysal, E., Ocak, G., & Ocak, I. (2020). Parents’ view of preschool children on eba and other distance education activities during the covid-19 outbreak. Journal of International Social Science Education, 6(2), 185-214. https://doi.org/10.47615/issej.835211
  • Alan, U. (2021). Distance education during the COVID-19 pandemic in Turkey: Identifying the needs of early childhood educators. Early Childhood Education Journal, 49, 987-994. https://doi.org/10.1007/s10643-021-01197-y
  • Aristovnik, A., Keržič, D., Ravšelj, D., Tomaževič, N., & Umek, L. (2020). Impacts of the COVID-19 pandemic on life of higher education students: A global perspective. Sustainability, 12(20), 8438. https://doi.org/10.3390/su12208438
  • Armitage, R., & Nellums, L. B. (2020). Considering inequalities in the school closure response to COVID-19. The Lancet, 8, e644. https://doi.org/10.1016/S2214-109X(20)30116-9
  • Ayda, K. N., Bastas, M., Altinay, F., Altinay, Z., & Dagli, G. (2020). Distance Education for Students with Special Needs in Primary Schools in the Period of CoVid-19 Epidemic. Propósitos y Representaciones, 8(3), e587. http://dx.doi.org/10.20511/pyr2020.v8n3.587
  • Barkur, G., Vibha, Kamath, & G. B. (2020). Sentiment analysis of nationwide lockdown due to COVID 19 outbreak: Evidence from India. Asian Journal of Psychiatry, 51, 1-2. https://doi.org/10.1016/j.ajp.2020.102089
  • Blei, D. M., Ng, A. Y., & Jordan, M. I. (2003). Latent dirichlet allocation. The Journal of Machine Learning Research, 3, 993-1022.
  • Bird, S., Klein, E., & Loper, E. (2009). Natural language processing with Python: Analyzing text with the natural language toolkit. O'Reilly Media, Inc.
  • Bostan, S., Erdem, R., Ozturk, Y. E., Kilic, T., & Yilmaz, A. (2020). The effect of COVID-19 pandemic on the Turkish society. Electronic Journal of General Medicine, 17(6), 1-8. https://doi.org/10.29333/ejgm/7944
  • Bozkurt, A., Jung, I., Xiao, J., Vladimirschi, V., Schuwer, R., Egorov, G., ... Paskevicius, M. (2020). A global outlook to the interruption of education due to COVID-19 pandemic: Navigating in a time of uncertainty and crisis. Asian Journal of Distance Education, 15(1), 1-126. https://doi.org/10.5281/zenodo.3878572
  • Calderón-Garrido, D., & Gustems-Carnicer, J. (2020). Adaptations of music education in primary and secondary school due to COVID-19: the experience in Spain. Music Education Research, 1-12. https://doi.org/10.1080/14613808.2021.1902488
  • Campos, M. M., & Vieira, L. F. (2020). COVID-19 and early childhood in Brazil: Impacts on children’s well-being, education and care. European Early Childhood Education Research Journal, 1-16. https://doi.org/10.1080/1350293X.2021.1872671
  • Chuang, J., Manning, C. D., & Heer, J. (2012). Termite: Visualization techniques for assessing textual topic models. Proceedings of the international working conference on advanced visual interfaces, 74-77. http://vis.stanford.edu/files/2012-Termite-AVI.pdf
  • Cicha, K., Rizun, M., Rutecka, P., & Strzelecki, A. (2021). COVID-19 and higher education: First-year students’ expectations towards distance learning. Sustainability, 13, 1889. https://doi.org/10.3390/su13041889
  • Crannell, W. C., Clark, E., Jones, C., James, T. A., & Moore, J. (2016). A pattern-matched Twitter analysis of US cancer-patient sentiments. Journal of Surgical Research, 206(2), 536-542. https://doi.org/10.1016/j.jss.2016.06.050
  • Deerwester, S., Dumais, S. T., Furnas, G. W., Landauer, T. K., & Harshman, R. (1990). Indexing by latent semantic analysis. Journal of the American Society for Information Science, 41(6), 391-407.
  • Ding, K., Li, J., & Zhang, Y. (2020). Hashtags, Emotions, and Comments: A large-scale dataset to understand fine-grained social emotions to online topics. Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing, 1376–1382. http://dx.doi.org/10.18653/v1/2020.emnlp-main.106
  • Dogan, S., & Kocak, E. (2020). A study on distance learning activities in the context of the EBA system. Journal of Economics and Social Research, 7(14), 110-124. http://www.ekosad.net/FileUpload/ep939088/File/42_soner_dogan.pdf
  • Duran, M. (2021). The effects of COVID-19 pandemic on preschool education. International Journal of Educational Methodology, 7(2), 249-260. https://doi.org/10.12973/ijem.7.2.249
  • Eutsler, L., Antonenko, P. D., & Mitchell, C. (2020). Initial response to COVID-19: A mixed-methods analysis of media and school communications to identify pedagogical implications for remote teaching. Interactive Technology and Smart Education, 18(2), 227-245. https://doi.org/10.1108/ITSE-08-2020-0159
  • Ewing, L-A., & Cooper, H. B. (2021). Technology-enabled remote learning during COVID-19: Perspectives of Australian teachers, students, and parents. Technology, Pedagogy, and Education, 30(1) 41-57. https://doi.org/10.1080/1475939X.2020.1868562
  • Foo, C., Cheung, B., & Chu, K. (2021). A comparative study regarding distance learning and the conventional face-to-face approach conducted problem-based learning tutorial during the COVID-19 pandemic. BMC Medical Education, 21(141), 1-6. https://doi.org/10.1186/s12909-021-02575-1
  • Goksoy, S. (2017). Pre-school educational process of Turkey. Open Journal of Social Sciences, 5, 73-83. https://doi.org/10.4236/jss.2017.53008
  • Gonzales, A. L., Calarco, J. M., & Lynch, T. (2020). Technology problems and student achievement gaps: A validation and extension of the technology maintenance construct. Communication Research, 47(5), 750-770. https://doi.org/10.1177%2F0093650218796366
  • Haider, M., & Yasmin, A. (2021). A gender base analysis of learners’ perceptions of online education in the context of Covid-19. Pakistan Journal of Gender Studies, 21(1), 33-62. https://doi.org/10.46568/pjgs.v21i1.514
  • Hodges, C., Moore, S., Lockee, B., Trust, T., & Bond, A. (2020, March 27). The difference between emergency remote teaching and online learning. EDUCAUSE Review. https://er.educause.edu/articles/2020/3/the-difference-between-emergency-remote-teaching-and-online-learning
  • Hofmann, T. (1999). Probabilistic latent semantic indexing. Proceedings of the 22nd annual international ACM SIGIR conference on research and development in information retrieval, 50-57. https://doi.org/10.1145/312624.312649
  • Inan, H. Z. (2020). Restructuring early childhood education during the COVID-19 pandemic. Milli Egitim, 49(1), 831-849. https://doi.org/10.37669/milliegitim.754307
  • Johnson, N., Veletsianos, G., & Seaman, J. (2020). U.S. faculty and administrators' experiences and approaches in the early weeks of the COVID-19 pandemic. Online Learning, 24(2), 6-21. https://doi.org/10.24059/olj.v24i2.2285
  • Khlaif, Z. N., Salha, S., & Kouraichi, B. (2021). Emergency remote learning during COVID-19 crisis: Students’ engagement. Education and Information Technologies, 26, 7033-7055. https://doi.org/10.1007/s10639-021-10566-4
  • Konca, A. S., & Cakir, T. (2021). Investigation of parents’ views on distance education of children’s transition from preschool education to primary school during the pandemic process. Journal of Education for Life, 35(2), 52-545. https://doi.org/10.33308/26674874.2021352307
  • Lesh, J. J. (2020). Navigating two pandemics: Racism/inequity and COVID-29: Thoughts from a former special education teacher. Teaching Exceptional Children, 53(1), 7-9.
  • Lytridis, C., Bazinas, C., Sidiropoulos, G., Papakostas, G. A., Kaburlasos, V. G., Nikopoulou, V.-A., Holeva, V., & Evangeliou, A. (2020). Distance special education delivery by social robots. Electronics, 9(6), 1034. https://doi.org/10.3390/electronics9061034
  • McFayden, T. C., Breaux, R., Bertollo, J. R., Cummings, K., & Ollendick, T. H. (2021). COVID-19 remote learning experiences of youth with neurodevelopmental disorders in rural appalachia. Journal of Rural Mental Health, 45(2), 72-85. https://doi.org/10.1037/rmh0000171
  • Means, B., Neisler, J., & Langer Research Associates. (2020). Suddenly online: A national survey of undergraduates during the COVID-19 pandemic. Digital Promise. https://digitalpromise.org/wp-content /uploads/ 2020/ 07/ ELE_CoBrand_DP_FINAL_3.pdf
  • Mungen, A. A., Aygun, I., & Kaya, M. (2020). Finding the relationship between news and social media users’ emotions in the COVID-19 process. Sakarya University Journal of Computer and Information Sciences, 3(3), 250-263. http://saucis.sakarya.edu.tr/en/download/article-file/1413664
  • Nazli, A. K., Kocaomer, C., Besbudak, M., & Koker, N. E. (2021). Understanding the initial reactions of Turkish Twitter users during the COVID-19 pandemic. The Turkish Online Journal of Design, Art and Communication, 11(1), 20-41. http://www.tojdac.org/tojdac/VOLUME11-ISSUE1_files/tojdac_v011i1102.pdf
  • Ozturk, N., & Ayvaz, S., (2018). Sentiment analysis on Twitter: A text mining approach to the Syrian refugee crisis. Telematics and Informatics, 35(1), 136-147. https://doi.org/10.1016/j.tele.2017.10.006
  • Parmigiani, D., Benigno, V., Giusto, M., Silvaggio, C., & Sperandio, S. (2020). E-inclusion: online special education in Italy during the Covid-19 pandemic. Technology, Pedagogy and Education, 30(1), 111-124. https://doi.org/10.1080/1475939X.2020.1856714
  • Pregowska, A., Masztalerz, K., Garlinska, M., & Osial, M. (2021). A worldwide journey through distance education-from the post office to virtual, augmented and mixed realities, and education during the COVID-19 pandemic. Education Sciences, 11(3), 118. https://doi.org/10.3390/educsci11030118
  • Psacharopoulos, G., Collis, V., Patrinos, H. A., & Vegas, E. (2020). Lost Wages: The COVID-19 Cost of School Closures. World Bank Policy Research Working Paper, 9246. World Bank. https://openknowledge.worldbank.org/handle/10986/34387
  • Rehurek, R., & Sojka, P. (2010). Software framework for topic modelling with large corpora. Proceedings of the LREC 2010 workshop on new challenges for NLP frameworks, 46-50. https://www.researchgate.net/publication/255820377_Software_Framework_for_Topic_Modelling_with_Large_Corpora
  • Robin, Dhiman, N., & Chauhan, A. (2020). A study on establishing the online teaching-learning for higher education during COVID-19 in India. Journal of Critical Reviews, 7(13), 4066-4075. https://www.bibliomed.org/mnsfulltext/197/197-1601619916.pdf?1639937284
  • Roy, S., & Ghosh, P. (2021). A comparative study on distancing, mask and vaccine adoption rates from global Twitter trends. Healthcare, 9, 488. https://doi.org/10.3390/healthcare9050488
  • Sahin, T., Gumus, H., & Gencoglu, C. (2021). Analysis of tweets related with physical activity during COVID-19 outbreak. Journal of Basic and Clinical Health Sciences, 1, 42-48. https://doi.org/10.30621/jbachs.869506
  • Sariman, G., & Mutaf, E. (2020). Sentiment analysis of Twitter messages in COVID-19 process. Eurasia Journal of Mathematics, Engineering, Natural & Medical Sciences, 7(10), 137-148. http://dx.doi.org/10.38065/euroasiaorg.149
  • Sider, S. R. (2020). School principles and students with special education needs in a pandemic: Emerging insights from Ontario, Canada. ISEA, 48(2), 78-84. https://www.thecommonwealth-educationhub.net/wp-content/uploads/2020/09/ISEA-2020-482.pdf#page=84
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There are 55 citations in total.

Details

Primary Language English
Subjects Studies on Education
Journal Section Articles
Authors

Secil Caskurlu 0000-0001-8716-9586

Serkan Ayvaz This is me 0000-0003-2016-4443

Kadir Kozan This is me 0000-0002-8241-5597

Early Pub Date April 30, 2023
Publication Date April 30, 2023
Published in Issue Year 2023 Volume: 7 Issue: Special Issue - Emerging Technologies and Technology Integration in Education

Cite

APA Caskurlu, S., Ayvaz, S., & Kozan, K. (2023). Sentiments towards Emergency Remote Teaching on Twitter: A Longitudinal Comparative Sentiment Analysis. Research on Education and Psychology, 7(Special Issue), 1-21. https://doi.org/10.54535/rep.1206924

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