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Social Media Mining for Health Research and Applications Workshop and Shared Tasks 2022: all accepted papers

54 papers · the most cited first · ← Social Media Mining for Health Research and Applications Workshop and Shared Tasks 2022

  1. AILAB-Udine@SMM4H'22: Limits of Transformers and BERT Ensembles ↗Beatrice Portelli, Simone Scaboro, Emmanuele Chersoni et al.
  2. AIR-JPMC@SMM4H'22: BERT + Ensembling = Too Cool: Using Multiple BERT Models Together for Various COVID-19 Tweet Identification Tasks ↗Leung Wai Liu, Akshat Gupta, Saheed Obitayo et al.
  3. AIR-JPMC@SMM4H'22: Classifying Self-Reported Intimate Partner Violence in Tweets with Multiple BERT-based Models ↗Alec Louis Candidato, Akshat Gupta, Xiaomo Liu et al.
  4. AIR-JPMC@SMM4H'22: Identifying Self-Reported Spanish COVID-19 Symptom Tweets Through Multiple-Model Ensembling ↗Adrian Garcia Hernandez, Leung Wai Liu, Akshat Gupta et al.
  5. ARGUABLY@SMM4H'22: Classification of Health Related Tweets using Ensemble, Zero-Shot and Fine-Tuned Language Model ↗Prabsimran Kaur, Guneet Kohli, Jatin Bedi
  6. BOUN-TABI@SMM4H'22: Text-to-Text Adverse Drug Event Extraction with Data Balancing and Prompting ↗Gökçe Uludoğan, Zeynep Yirmibeşoğlu
  7. BioInfo@UAVR@SMM4H'22: Classification and Extraction of Adverse Event mentions in Tweets using Transformer Models ↗Edgar Morais, José Luis Oliveira, Alina Trifan et al.
  8. CAISA@SMM4H'22: Robust Cross-Lingual Detection of Disease Mentions on Social Media with Adversarial Methods ↗Akbar Karimi, Lucie Flek
  9. CASIA@SMM4H'22: A Uniform Health Information Mining System for Multilingual Social Media Texts ↗Jia Fu, Sirui Li, Hui Ming Yuan et al.
  10. CHAAI@SMM4H'22: RoBERTa, GPT-2 and Sampling - An interesting concoction ↗Christopher Palmer, Sedigheh Khademi Habibabadi, Muhammad Javed et al.
  11. CIC NLP at SMM4H 2022: a BERT-based approach for classification of social media forum posts ↗Atnafu Lambebo Tonja, Olumide Ebenezer Ojo, Mohammed Arif Khan et al.
  12. CLaCLab at SocialDisNER: Using Medical Gazetteers for Named-Entity Recognition of Disease Mentions in Spanish Tweets ↗Harsh Verma, Parsa Bagherzadeh, Sabine Bergler
  13. COVID-19-related Nepali Tweets Classification in a Low Resource Setting ↗Rabin Adhikari, Safal Thapaliya, Nirajan Basnet et al.
  14. CSECU-DSG@SMM4H'22: Transformer based Unified Approach for Classification of Changes in Medication Treatments in Tweets and WebMD Reviews ↗Afrin Sultana, Nihad Karim Chowdhury, Abu Nowshed Chy
  15. CompLx@SMM4H'22: In-domain pretrained language models for detection of adverse drug reaction mentions in English tweetsOrest Xherija, Hojoon Choiour summary
  16. 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 ↗Imane Guellil, Jinge Wu, Honghan Wu et al.
  17. Enolp musk@SMM4H'22 : Leveraging Pre-trained Language Models for Stance And Premise Classification ↗Millon Madhur Das, Archit Mangrulkar, Ishan Manchanda et al.
  18. FRE at SocialDisNER: Joint Learning of Language Models for Named Entity Recognition ↗Kendrick Cetina, Nuria García-Santa
  19. Fraunhofer FKIE @ SMM4H 2022: System Description for Shared Tasks 2, 4 and 9 ↗Daniel Claeser, Samantha Kent
  20. Fraunhofer SIT@SMM4H'22: Learning to Predict Stances and Premises in Tweets related to COVID-19 Health Orders Using Generative Models ↗Raphael Frick, Martin Steinebach
  21. HaleLab_NITK@SMM4H'22: Adaptive Learning Model for Effective Detection, Extraction and Normalization of Adverse Drug Events from Social Media Data ↗Reshma Unnikrishnan, Sowmya Kamath S, Ananthanarayana V. S.
  22. IAI @ SocialDisNER : Catch me if you can! Capturing complex disease mentions in tweets ↗Aman Sinha, Cristina Garcia Holgado, Marianne Clausel et al.
  23. ITAINNOVA at SocialDisNER: A Transformers cocktail for disease identification in social media in Spanish ↗Rosa Montañés-Salas, Irene López-Bosque, Luis García-Garcés et al.
  24. Innovators @ SMM4H'22: An Ensembles Approach for self-reporting of COVID-19 Vaccination Status Tweets ↗Mohammad Zohair, Nidhir Bhavsar, Aakash Bhatnagar et al.
  25. Innovators@SMM4H'22: An Ensembles Approach for Stance and Premise Classification of COVID-19 Health Mandates Tweets ↗Vatsal Savaliya, Aakash Bhatnagar, Nidhir Bhavsar et al.
  26. John_Snow_Labs@SMM4H'22: Social Media Mining for Health (\#SMM4H) with Spark NLP ↗Veysel Kocaman, Cabir Celik, Damla Gurbaz et al.
  27. KUL@SMM4H'22: Template Augmented Adaptive Pre-training for Tweet Classification ↗Sumam Francis, Marie-Francine Moens
  28. KU_ED at SocialDisNER: Extracting Disease Mentions in Tweets Written in Spanish ↗Antoine Lain, Wonjin Yoon, Hyunjae Kim et al.
  29. Leveraging Social Media as a Source for Clinical Guidelines: A Demarcation of Experiential Knowledge ↗Jia-Zhen Michelle Chan, Florian Kunneman, Roser Morante et al.
  30. MANTIS at SMM4H'2022: Pre-Trained Language Models Meet a Suite of Psycholinguistic Features for the Detection of Self-Reported Chronic Stress ↗Sourabh Zanwar, Daniel Wiechmann, Yu Qiao et al.
  31. MaNLP@SMM4H'22: BERT for Classification of Twitter Posts ↗Keshav Kapur, Rajitha Harikrishnan, Sanjay Singh
  32. NCUEE-NLP@SMM4H'22: Classification of Self-reported Chronic Stress on Twitter Using Ensemble Pre-trained Transformer Models ↗Tzu-Mi Lin, Chao-Yi Chen, Yu-Wen Tzeng et al.
  33. NLP-CIC-WFU at SocialDisNER: Disease Mention Extraction in Spanish Tweets Using Transfer Learning and Search by Propagation ↗Antonio Tamayo, Alexander Gelbukh, Diego Burgos
  34. OFU@SMM4H'22: Mining Advent Drug Events Using Pretrained Language Models ↗Omar Adjali, Fréjus A. A. Laleye, Umang Aggarwal
  35. Overview of the Seventh Social Media Mining for Health Applications (\#SMM4H) Shared Tasks at COLING 2022 ↗Davy Weissenbacher, Juan Banda, Vera Davydova et al.
  36. PLN CMM at SocialDisNER: Improving Detection of Disease Mentions in Tweets by Using Document-Level Features ↗Matias Rojas, Jose Barros, Kinan Martin et al.
  37. PingAnTech at SMM4H task1: Multiple pre-trained model approaches for Adverse Drug Reactions ↗Xi Liu, Han Zhou, Chang Su
  38. RACAI@SMM4H'22: Tweets Disease Mention Detection Using a Neural Lateral Inhibitory Mechanism ↗Andrei-Marius Avram, Vasile Pais, Maria Mitrofan
  39. READ-BioMed@SocialDisNER: Adaptation of an Annotation System to Spanish Tweets ↗Antonio Jimeno Yepes, Karin Verspoor
  40. Romanian micro-blogging named entity recognition including health-related entities ↗Vasile Pais, Verginica Barbu Mititelu, Elena Irimia et al.
  41. SINAI@SMM4H'22: Transformers for biomedical social media text mining in Spanish ↗Mariia Chizhikova, Pilar López-Úbeda, Manuel C. Díaz-Galiano et al.
  42. SMM4H 2022 Task 2: Dataset for stance and premise detection in tweets about health mandates related to COVID-19 ↗Vera Davydova, Elena Tutubalina
  43. The Best of Both Worlds: Combining Engineered Features with Transformers for Improved Mental Health Prediction from Reddit Posts ↗Sourabh Zanwar, Daniel Wiechmann, Yu Qiao et al.
  44. The SocialDisNER shared task on detection of disease mentions in health-relevant content from social media: methods, evaluation, guidelines and corpora ↗Luis Gasco Sánchez, Darryl Estrada Zavala, Eulàlia Farré-Maduell et al.
  45. Transformer-based classification of premise in tweets related to COVID-19 ↗Vadim Porvatov, Natalia Semenova
  46. UB Health Miners@SMM4H'22: Exploring Pre-processing Techniques To Classify Tweets Using Transformer Based Pipelines. ↗Roshan Khatri, Sougata Saha, Souvik Das et al.
  47. UCCNLP@SMM4H'22:Label distribution aware long-tailed learning with post-hoc posterior calibration applied to text classification ↗Paul Trust, Provia Kadusabe, Ahmed Zahran et al.
  48. Yet@SMM4H'22: Improved BERT-based classification models with Rdrop and PolyLoss ↗Yan Zhuang, Yanru Zhang
  49. Zhegu@SMM4H-2022: The Pre-training Tweet & Claim Matching Makes Your Prediction Better ↗Pan He, Chen YuZe, Yanru Zhang
  50. dezzai@SMM4H'22: Tasks 5 & 10 - Hybrid models everywhere ↗Miguel Ortega-Martín, Alfonso Ardoiz, Oscar Garcia et al.
  51. mattica@SMM4H'22: Leveraging sentiment for stance & premise joint learning ↗Oscar Lithgow-Serrano, Joseph Cornelius, Fabio Rinaldi et al.
  52. uestcc@SMM4H'22: RoBERTa based Adverse Drug Events Classification on Tweets ↗Chunchen Wei, Ran Bi, Yanru Zhang
  53. yiriyou@SMM4H'22: Stance and Premise Classification in Domain Specific Tweets with Dual-View Attention Neural Networks ↗Huabin Yang, Zhongjian Zhang, Yanru Zhang
  54. zydhjh4593@SMM4H'22: A Generic Pre-trained BERT-based Framework for Social Media Health Text Classification ↗Chenghao Huang, Xiaolu Chen, Yuxi Chen et al.

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