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Streamlining Social Media Information Retrieval for COVID-19 Research with Deep Learning
March 19, 2024, 4:54 a.m. | Yining Hua, Jiageng Wu, Shixu Lin, Minghui Li, Yujie Zhang, Dinah Foer, Siwen Wang, Peilin Zhou, Jie Yang, Li Zhou
cs.CL updates on arXiv.org arxiv.org
Abstract: Objective: Social media-based public health research is crucial for epidemic surveillance, but most studies identify relevant corpora with keyword-matching. This study develops a system to streamline the process of curating colloquial medical dictionaries. We demonstrate the pipeline by curating a UMLS-colloquial symptom dictionary from COVID-19-related tweets as proof of concept. Methods: COVID-19-related tweets from February 1, 2020, to April 30, 2022 were used. The pipeline includes three modules: a named entity recognition module to detect …
abstract arxiv covid covid-19 cs.ai cs.cl cs.ir deep learning dictionary epidemic health health research identify information media medical pipeline process public public health research retrieval social social media studies study surveillance type
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