@inproceedings{gencoglu-2020-sentence,
    title = "Sentence Transformers and {B}ayesian Optimization for Adverse Drug Effect Detection from {T}witter",
    author = "Gencoglu, Oguzhan",
    editor = "Gonzalez-Hernandez, Graciela  and
      Klein, Ari Z.  and
      Flores, Ivan  and
      Weissenbacher, Davy  and
      Magge, Arjun  and
      O'Connor, Karen  and
      Sarker, Abeed  and
      Minard, Anne-Lyse  and
      Tutubalina, Elena  and
      Miftahutdinov, Zulfat  and
      Alimova, Ilseyar",
    booktitle = "Proceedings of the Fifth Social Media Mining for Health Applications Workshop {\&} Shared Task",
    month = dec,
    year = "2020",
    address = "Barcelona, Spain (Online)",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/ingest-emnlp/2020.smm4h-1.30/",
    pages = "161--164",
    abstract = "This paper describes our approach for detecting adverse drug effect mentions on Twitter as part of the Social Media Mining for Health Applications (SMM4H) 2020, Shared Task 2. Our approach utilizes multilingual sentence embeddings (sentence-BERT) for representing tweets and Bayesian hyperparameter optimization of sample weighting parameter for counterbalancing high class imbalance."
}