Abstract
Limited research exists on how experts’ Systems Thinking (ST) skills can be linked to their tweets and sentiments. This study employs text mining and social media analysis to explore the relationship between experts’ ST and their tweets, specifically focusing on COVID-19. Twitter is crucial for information dissemination, but misinformation can spread during a pandemic like COVID-19. By analyzing the emotional and sentimental aspects of tweets from 55 COVID-19 experts, we identified three distinct clusters with significant differences in emotions and sentiments. This study introduces a novel framework using NLP, text mining, and sentiment analysis to assess the systems thinking skills of COVID-19 experts.
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Nagahisarchoghaei, M., Nagahi, M., Pirim, H. (2024). Text Mining and Sentimental Analysis to Distinguish Systems Thinkers at Various Levels: A Case Study of COVID-19. In: García Márquez, F.P., Jamil, A., Hameed, A.A., Segovia Ramírez, I. (eds) Emerging Trends and Applications in Artificial Intelligence. ICETAI 2023. Lecture Notes in Networks and Systems, vol 960. Springer, Cham. https://doi.org/10.1007/978-3-031-56728-5_7
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DOI: https://doi.org/10.1007/978-3-031-56728-5_7
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