Temporal analysis of topic modeling output by machine learning techniques
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Publisher
Springer Science and Business Media LLC
Link
https://link.springer.com/content/pdf/10.1007/s41060-024-00583-0.pdf
Reference33 articles.
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3. Azizi, F., Hajiabadi, H., Vahdat-Nejad, H., Khosravi, M.H.: Detecting and analyzing topics of massive COVID-19 related tweets for various countries. Comput. Electr. Eng. 106, 1–11 (2023)
4. Palanichamy, Y., Kargar, M., Zolfagharinia, H.: Unearthing trends in environmental science and engineering research: insights from a probabilistic topic modeling literature analysis. J. Clean. Prod. 317, 1–21 (2021)
5. Xie, Y., Ning, C., Sun, L.: The twenty-first century of structural engineering research: a topic modeling approach. Structures 35, 577–590 (2022)
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