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ORCID7th SMM4H 2022: Gyeongju, Korea
- Graciela Gonzalez-Hernandez, Davy Weissenbacher:
Proceedings of The Seventh Workshop on Social Media Mining for Health Applications, Workshop & Shared Task, SMM4H@COLING 2022, Gyeongju, Republic of Korea, October 12 - 17, 2022. Association for Computational Linguistics 2022 - Frontmatter.
- Andrei-Marius Avram, Vasile Pais, Maria Mitrofan:
RACAI@SMM4H'22: Tweets Disease Mention Detection Using a Neural Lateral Inhibitory Mechanism. 1-3 - Xi Liu, Han Zhou, Chang Su:
PingAnTech at SMM4H task1: Multiple pre-trained model approaches for Adverse Drug Reactions. 4-6 - Miguel Ortega-Martín, Alfonso Ardoiz, Oscar Garcia, Jorge Álvarez, Adrián Alonso:
dezzai@SMM4H'22: Tasks 5 & 10 - Hybrid models everywhere. 7-10 - Chenghao Huang, Xiaolu Chen, Yuxi Chen, Yutong Wu, Weimin Yuan, Yan Wang, Yanru Zhang:
zydhjh4593@SMM4H'22: A Generic Pre-trained BERT-based Framework for Social Media Health Text Classification. 11-15 - Sourabh Zanwar, Daniel Wiechmann, Yu Qiao, Elma Kerz:
MANTIS at SMM4H'2022: Pre-Trained Language Models Meet a Suite of Psycholinguistic Features for the Detection of Self-Reported Chronic Stress. 16-18 - Antonio Tamayo, Alexander F. Gelbukh, Diego A. Burgos:
NLP-CIC-WFU at SocialDisNER: Disease Mention Extraction in Spanish Tweets Using Transfer Learning and Search by Propagation. 19-22 - Huabin Yang, Zhongjian Zhang, Yanru Zhang:
yiriyou@SMM4H'22: Stance and Premise Classification in Domain Specific Tweets with Dual-View Attention Neural Networks. 23-26 - Mariia Chizhikova
, Pilar López-Úbeda, Manuel Carlos Díaz-Galiano, Luis Alfonso Ureña López, María Teresa Martín Valdivia:
SINAI@SMM4H'22: Transformers for biomedical social media text mining in Spanish. 27-30 - Gökçe Uludogan, Zeynep Yirmibesoglu:
BOUN-TABI@SMM4H'22: Text-to-Text Adverse Drug Event Extraction with Data Balancing and Prompting. 31-34 - Chunchen Wei, Ran Bi, Yanru Zhang:
uestcc@SMM4H'22: RoBERTa based Adverse Drug Events Classification on Tweets. 35-37 - Pan He, Yuze Chen, Yanru Zhang:
Zhegu@SMM4H-2022: The Pre-training Tweet & Claim Matching Makes Your Prediction Better. 38-41 - Keshav Kapur, Rajitha Harikrishnan, Sanjay Singh:
MaNLP@SMM4H'22: BERT for Classification of Twitter Posts. 42-43 - Veysel Kocaman, Cabir Celik, Damla Gurbaz, Gursev Pirge, Bunyamin Polat, Halil Saglamlar, Meryem Vildan Sarikaya, Gokhan Turer, David Talby:
John_Snow_Labs@SMM4H'22: Social Media Mining for Health (#SMM4H) with Spark NLP. 44-47 - Antonio Jimeno-Yepes, Karin Verspoor:
READ-BioMed@SocialDisNER: Adaptation of an Annotation System to Spanish Tweets. 48-51 - Matías Rojas, Jose Barros, Kinan Martin, Mauricio Araneda-Hernandez, Jocelyn Dunstan:
PLN CMM at SocialDisNER: Improving Detection of Disease Mentions in Tweets by Using Document-Level Features. 52-54 - Harsh Verma, Parsa Bagherzadeh, Sabine Bergler:
CLaCLab at SocialDisNER: Using Medical Gazetteers for Named-Entity Recognition of Disease Mentions in Spanish Tweets. 55-57 - Atnafu Lambebo Tonja, Olumide Ebenezer Ojo, Mohammed Arif Khan, Abdul Gafar Manuel Meque, Olga Kolesnikova, Grigori Sidorov, Alexander F. Gelbukh:
CIC NLP at SMM4H 2022: a BERT-based approach for classification of social media forum posts. 58-61 - Tzu-Mi Lin, Chao-Yi Chen, Yu-Wen Tzeng, Lung-Hao Lee:
NCUEE-NLP@SMM4H'22: Classification of Self-reported Chronic Stress on Twitter Using Ensemble Pre-trained Transformer Models. 62-64 - Edgar Morais, José Luís Oliveira, Alina Trifan, Olga Fajarda:
BioInfo@UAVR@SMM4H'22: Classification and Extraction of Adverse Event mentions in Tweets using Transformer Models. 65-67 - Kendrick Cetina, Nuria García-Santa:
FRE at SocialDisNER: Joint Learning of Language Models for Named Entity Recognition. 68-70 - Rosa María Montañés-Salas, Irene López-Bosque, Luis García-Garcés, Rafael del-Hoyo-Alonso:
ITAINNOVA at SocialDisNER: A Transformers cocktail for disease identification in social media in Spanish. 71-74 - Oscar Lithgow-Serrano, Joseph Cornelius, Fabio Rinaldi, Ljiljana Dolamic:
mattica@SMM4H'22: Leveraging sentiment for stance & premise joint learning. 75-77 - Antoine Lain, Wonjin Yoon, Hyunjae Kim, Jaewoo Kang, Ian Simpson:
KU_ED at SocialDisNER: Extracting Disease Mentions in Tweets Written in Spanish. 78-80 - Christopher Palmer, Sedigheh Khademi Habibabadi, Muhammad Javed, Gerardo Luis Dimaguila, Jim Buttery:
CHAAI@SMM4H'22: RoBERTa, GPT-2 and Sampling - An interesting concoction. 81-84 - Aman Sinha, Cristina García Holgado, Marianne Clausel, Matthieu Constant:
IAI @ SocialDisNER : Catch me if you can! Capturing complex disease mentions in tweets. 85-89 - Paul Trust, Provia Kadusabe, Ahmed Zahran, Rosane Minghim, Kizito Omala:
UCCNLP@SMM4H'22: Label distribution aware long-tailed learning with post-hoc posterior calibration applied to text classification. 90-94 - Reshma Unnikrishnan, Sowmya Kamath S., Ananthanarayana V. S.:
HaleLab_NITK@SMM4H'22: Adaptive Learning Model for Effective Detection, Extraction and Normalization of Adverse Drug Events from Social Media Data. 95-97 - Yan Zhuang, Yanru Zhang:
Yet@SMM4H'22: Improved BERT-based classification models with Rdrop and PolyLoss. 98-102 - Daniel Claeser, Samantha Kent:
Fraunhofer FKIE @ SMM4H 2022: System Description for Shared Tasks 2, 4 and 9. 103-107 - Vadim Porvatov, Natalia Semenova:
Transformer-based classification of premise in tweets related to COVID-19. 108-110 - Raphael Antonius Frick, Martin Steinebach:
Fraunhofer SIT@SMM4H'22: Learning to Predict Stances and Premises in Tweets related to COVID-19 Health Orders Using Generative Models. 111-113 - Roshan Khatri, Sougata Saha, Souvik Das, Rohini K. Srihari:
UB Health Miners@SMM4H'22: Exploring Pre-processing Techniques To Classify Tweets Using Transformer Based Pipelines. 114-117 - Afrin Sultana, Nihad Karim Chowdhury, Abu Nowshed Chy:
CSECU-DSG@SMM4H'22: Transformer based Unified Approach for Classification of Changes in Medication Treatments in Tweets and WebMD Reviews. 118-122 - Mohammad Zohair, Nidhir Bhavsar, Aakash Bhatnagar, Muskaan Singh:
Innovators @ SMM4H'22: An Ensembles Approach for self-reporting of COVID-19 Vaccination Status Tweets. 123-125 - Vatsal Savaliya, Aakash Bhatnagar, Nidhir Bhavsar, Muskaan Singh:
Innovators@SMM4H'22: An Ensembles Approach for Stance and Premise Classification of COVID-19 Health Mandates Tweets. 126-129 - Beatrice Portelli, Simone Scaboro, Emmanuele Chersoni, Enrico Santus, Giuseppe Serra:
AILAB-Udine@SMM4H'22: Limits of Transformers and BERT Ensembles. 130-134 - Alec Louis Candidato, Akshat Gupta, Xiaomo Liu, Sameena Shah:
AIR-JPMC@SMM4H'22: Classifying Self-Reported Intimate Partner Violence in Tweets with Multiple BERT-based Models. 135-137 - Prabsimran Kaur, Guneet Singh Kohli, Jatin Bedi:
ARGUABLY@SMM4H'22: Classification of Health Related Tweets using Ensemble, Zero-Shot and Fine-Tuned Language Model. 138-142 - Jia Fu, Sirui Li, Hui Ming Yuan, Zhucong Li, Zhen Gan, Yubo Chen, Kang Liu, Jun Zhao, Shengping Liu:
CASIA@SMM4H'22: A Uniform Health Information Mining System for Multilingual Social Media Texts. 143-147 - Imane Guellil, Jinge Wu, Honghan Wu, Tony Sun, Beatrice Alex:
Edinburgh_UCL_Health@SMM4H'22: From Glove to Flair for handling imbalanced healthcare corpora related to Adverse Drug Events, Change in medication and self-reporting vaccination. 148-152 - Sumam Francis, Marie-Francine Moens:
KUL@SMM4H'22: Template Augmented Adaptive Pre-training for Tweet Classification. 153-155 - Millon Das, Archit Mangrulkar, Ishan Manchanda, Manav Nitin Kapadnis, Sohan Patnaik:
Enolp musk@SMM4H'22 : Leveraging Pre-trained Language Models for Stance And Premise Classification. 156-159 - Adrian Garcia Hernandez, Leung Wai Liu, Akshat Gupta, Vineeth Ravi, Saheed O. Obitayo, Xiaomo Liu, Sameena Shah:
AIR-JPMC@SMM4H'22: Identifying Self-Reported Spanish COVID-19 Symptom Tweets Through Multiple-Model Ensembling. 160-162 - Leung Wai Liu, Akshat Gupta, Saheed Obitayo, Xiaomo Liu, Sameena Shah:
AIR-JPMC@SMM4H'22: BERT + Ensembling = Too Cool: Using Multiple BERT Models Together for Various COVID-19 Tweet Identification Tasks. 163-167 - Akbar Karimi, Lucie Flek:
CAISA@SMM4H'22: Robust Cross-Lingual Detection of Disease Mentions on Social Media with Adversarial Methods. 168-170 - Omar Adjali, Fréjus A A Laleye, Umang Aggarwal:
OFU@SMM4H'22: Mining Advent Drug Events Using Pretrained Language Models. 171-175 - Orest Xherija, Hojoon Choi:
CompLx@SMM4H'22: In-domain pretrained language models for detection of adverse drug reaction mentions in English tweets. 176-181 - Luis Gascó Sánchez, Darryl Estrada-Zavala, Eulàlia Farré-Maduell, Salvador Lima-López, Antonio Miranda-Escalada, Martin Krallinger:
The SocialDisNER shared task on detection of disease mentions in health-relevant content from social media: methods, evaluation, guidelines and corpora. 182-189 - Vasile Pais, Verginica Barbu Mititelu, Elena Irimia, Maria Mitrofan, Carol Luca Gasan, Roxana Micu:
Romanian micro-blogging named entity recognition including health-related entities. 190-196 - Sourabh Zanwar, Daniel Wiechmann, Yu Qiao, Elma Kerz:
The Best of Both Worlds: Combining Engineered Features with Transformers for Improved Mental Health Prediction from Reddit Posts. 197-202 - Jia-Zhen Michelle Chan, Florian Kunneman, Roser Morante, Lea Lösch, Teun Zuiderent-Jerak:
Leveraging Social Media as a Source for Clinical Guidelines: A Demarcation of Experiential Knowledge. 203-208 - Rabin Adhikari, Safal Thapaliya, Nirajan Basnet, Samip Poudel, Aman Shakya, Bishesh Khanal:
COVID-19-related Nepali Tweets Classification in a Low Resource Setting. 209-215 - Vera Davydova, Elena Tutubalina:
SMM4H 2022 Task 2: Dataset for stance and premise detection in tweets about health mandates related to COVID-19. 216-220 - Davy Weissenbacher, Juan M. Banda, Vera Davydova, Darryl Estrada-Zavala, Luis Gascó Sánchez, Yao Ge, Yuting Guo, Ari Z. Klein, Martin Krallinger, Mathias Leddin, Arjun Magge, Raul Rodriguez-Esteban, Abeed Sarker, Ana Lucía Schmidt, Elena Tutubalina, Graciela Gonzalez-Hernandez:
Overview of the Seventh Social Media Mining for Health Applications (#SMM4H) Shared Tasks at COLING 2022. 221-241
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