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ORCID5th SMM4H@COLING 2020: Barcelona, Spain (Online)
- Graciela Gonzalez-Hernandez, Ari Z. Klein, Ivan Flores, Davy Weissenbacher, Arjun Magge, Karen O'Connor, Abeed Sarker, Anne-Lyse Minard, Elena Tutubalina, Zulfat Miftahutdinov, Ilseyar Alimova:
Proceedings of the Fifth Social Media Mining for Health Applications Workshop & Shared Task, SMM4H@COLING 2020, Barcelona, Spain (Online), December 12, 2020. Association for Computational Linguistics 2020, ISBN 978-1-952148-41-5 - Joseph Cornelius, Tilia Ellendorff, Lenz Furrer, Fabio Rinaldi:
COVID-19 Twitter Monitor: Aggregating and Visualizing COVID-19 Related Trends in Social Media. 1-10 - Anne Dirkson, Suzan Verberne, Wessel Kraaij:
Conversation-Aware Filtering of Online Patient Forum Messages. 11-18 - Julia Romberg
, Jan Dyczmons, Sandra Olivia Borgmann, Jana Sommer, Markus Vomhof, Cecilia Brunoni, Ismael Bruck-Ramisch, Luis Enders, Andrea Icks, Stefan Conrad:
Annotating Patient Information Needs in Online Diabetes Forums. 19-26 - Ari Z. Klein, Ilseyar Alimova, Ivan Flores, Arjun Magge, Zulfat Miftahutdinov, Anne-Lyse Minard, Karen O'Connor, Abeed Sarker, Elena Tutubalina, Davy Weissenbacher, Graciela Gonzalez-Hernandez:
Overview of the Fifth Social Media Mining for Health Applications (#SMM4H) Shared Tasks at COLING 2020. 27-36 - Huong Dang, Kahyun Lee, Sam Henry, Özlem Uzuner:
Ensemble BERT for Classifying Medication-mentioning Tweets. 37-41 - Chen-Kai Wang, Hong-Jie Dai, You-Chen Zhang, Bo-Chun Xu, Bo-Hong Wang, You-Ning Xu, Po-Hao Chen, Chung-Hong Lee:
ISLab System for SMM4H Shared Task 2020. 42-45 - Andrey Gusev, Anna Kuznetsova, Anna Polyanskaya, Egor Yatsishin:
BERT Implementation for Detecting Adverse Drug Effects Mentions in Russian. 46-50 - Zulfat Miftahutdinov, Andrey Sakhovskiy, Elena Tutubalina:
KFU NLP Team at SMM4H 2020 Tasks: Cross-lingual Transfer Learning with Pretrained Language Models for Drug Reactions. 51-56 - Isabel Metzger, Emir Y. Haskovic, Allison Black, Whitley M. Yi, Rajat S. Chandra, Mark T. Rutledge, William McMahon, Yindalon Aphinyanaphongs:
SMM4H Shared Task 2020 - A Hybrid Pipeline for Identifying Prescription Drug Abuse from Twitter: Machine Learning, Deep Learning, and Post-Processing. 57-62 - Yang Bai, Xiaobing Zhou:
Automatic Detecting for Health-related Twitter Data with BioBERT. 63-69 - Luis Moßburger, Felix Wende, Kay Brinkmann, Thomas Schmidt:
Exploring Online Depression Forums via Text Mining: A Comparison of Reddit and a Curated Online Forum. 70-81 - David Owen, José Camacho-Collados, Luis Espinosa Anke:
Towards Preemptive Detection of Depression and Anxiety in Twitter. 82-89 - V. G. Vinod Vydiswaran, Deahan Yu, Xinyan Zhao, Ermioni Carr, Jonathan Martindale, Jingcheng Xiao, Noha Ghannam, Matteo Althoen, Alexis Castellanos, Neel Patel, Daniel Vasquez:
Identifying Medication Abuse and Adverse Effects from Tweets: University of Michigan at #SMM4H 2020. 90-94 - Lucie Gattepaille:
How Far Can We Go with Just Out-of-the-box BERT Models? 95-100 - Silvia Casola, Alberto Lavelli:
FBK@SMM4H2020: RoBERTa for Detecting Medications on Twitter. 101-103 - Sougata Saha, Souvik Das, Prashi Khurana, Rohini K. Srihari:
Autobots Ensemble: Identifying and Extracting Adverse Drug Reaction from Tweets Using Transformer Based Pipelines. 104-109 - Pavel Blinov, Manvel Avetisian:
Transformer Models for Drug Adverse Effects Detection from Tweets. 110-112 - Sedigheh Khademi, Pari Delir Haghighi, Frada Burstein:
Adverse Drug Reaction Detection in Twitter Using RoBERTa and Rules. 113-117 - Mohamed Lichouri, Mourad Abbas:
SpeechTrans@SMM4H'20: Impact of Preprocessing and N-grams on Automatic Classification of Tweets That Mention Medications. 118-120 - Katikapalli Subramanyam Kalyan, Sivanesan Sangeetha:
Want to Identify, Extract and Normalize Adverse Drug Reactions in Tweets? Use RoBERTa. 121-124 - Saichethan Reddy:
Detecting Tweets Reporting Birth Defect Pregnancy Outcome Using Two-View CNN RNN Based Architecture. 125-127 - Yandrapati Prakash Babu, Eswari Rajagopal:
Identification of Medication Tweets Using Domain-specific Pre-trained Language Models. 128-130 - Lung-Hao Lee, Po-Han Chen, Hao-Chuan Kao, Ting-Chun Hung, Po-Lei Lee, Kuo-Kai Shyu:
Medication Mention Detection in Tweets Using ELECTRA Transformers and Decision Trees. 131-133 - Ludovic Tanguy, Lydia-Mai Ho-Dac, Cécile Fabre, Roxane Bois, Touati Mohamed Yacine Haddad, Claire Ibarboure, Marie Joyau, François Le moal, Jade Moiilic, Laura Roudaut, Mathilde Simounet, Irena Stankovic, Mickaela Vandewaetere:
LITL at SMM4H: An Old-school Feature-based Classifier for Identifying Adverse Effects in Tweets. 134-137 - Farhana Ferdousi Liza:
Sentence Classification with Imbalanced Data for Health Applications. 138-145 - Xiaoyu Zhao, Ying Xiong, Buzhou Tang:
HITSZ-ICRC: A Report for SMM4H Shared Task 2020-Automatic Classification of Medications and Adverse Effect in Tweets. 146-149 - Laiba Mehnaz:
Automatic Classification of Tweets Mentioning a Medication Using Pre-trained Sentence Encoders. 150-152 - George-Andrei Dima, Andrei-Marius Avram, Dumitru-Clementin Cercel:
Approaching SMM4H 2020 with Ensembles of BERT Flavours. 153-157 - Darshini Mahendran, Cora Lewis, Bridget T. McInnes:
NLP@VCU: Identifying Adverse Effects in English Tweets for Unbalanced Data. 158-160 - Oguzhan Gencoglu:
Sentence Transformers and Bayesian Optimization for Adverse Drug Effect Detection from Twitter. 161-164 - Olanrewaju Tahir Aduragba, Jialin Yu, Gautham Senthilnathan, Alexandra Crsitea:
Sentence Contextual Encoder with BERT and BiLSTM for Automatic Classification with Imbalanced Medication Tweets. 165-167 - Parsa Bagherzadeh, Sabine Bergler:
CLaC at SMM4H 2020: Birth Defect Mention Detection. 168-170
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