Identification and Analysis of COVID-19-related Misinformation Tweets via Kullback-Leibler Divergence for Informativeness and Phraseness and Biterm Topic Modeling

Thomas Daniel S. Clamor, Geoffrey A. Solano, Nathaniel Oco, Jasper Kyle Catapang, Jerome V. Cleofas, Iris Thiele Isip-Tan. Identification and Analysis of COVID-19-related Misinformation Tweets via Kullback-Leibler Divergence for Informativeness and Phraseness and Biterm Topic Modeling. In 2022 International Conference on Artificial Intelligence in Information and Communication, ICAIIC 2022, Jeju Island, Korea, Republic of, February 21-24, 2022. pages 451-456, IEEE, 2022. [doi]

@inproceedings{ClamorSOCCI22,
  title = {Identification and Analysis of COVID-19-related Misinformation Tweets via Kullback-Leibler Divergence for Informativeness and Phraseness and Biterm Topic Modeling},
  author = {Thomas Daniel S. Clamor and Geoffrey A. Solano and Nathaniel Oco and Jasper Kyle Catapang and Jerome V. Cleofas and Iris Thiele Isip-Tan},
  year = {2022},
  doi = {10.1109/ICAIIC54071.2022.9722623},
  url = {https://doi.org/10.1109/ICAIIC54071.2022.9722623},
  researchr = {https://researchr.org/publication/ClamorSOCCI22},
  cites = {0},
  citedby = {0},
  pages = {451-456},
  booktitle = {2022 International Conference on Artificial Intelligence in Information and Communication, ICAIIC 2022, Jeju Island, Korea, Republic of, February 21-24, 2022},
  publisher = {IEEE},
  isbn = {978-1-6654-5818-4},
}