Atul Kr. Ojha, P. Rani, Koustava Goswami, Bharathi Raja Chakravarthi, John P. Mccrae
{"title":"ULD-NUIG at Social Media Mining for Health Applications (#SMM4H) Shared Task 2021","authors":"Atul Kr. Ojha, P. Rani, Koustava Goswami, Bharathi Raja Chakravarthi, John P. Mccrae","doi":"10.18653/V1/2021.SMM4H-1.33","DOIUrl":null,"url":null,"abstract":"Social media platforms such as Twitter and Facebook have been utilised for various research studies, from the cohort-level discussion to community-driven approaches to address the challenges in utilizing social media data for health, clinical and biomedical information. Detection of medical jargon’s, named entity recognition, multi-word expression becomes the primary, fundamental steps in solving those challenges. In this paper, we enumerate the ULD-NUIG team’s system, designed as part of Social Media Mining for Health Applications (#SMM4H) Shared Task 2021. The team conducted a series of experiments to explore the challenges of task 6 and task 5. The submitted systems achieve F-1 0.84 and 0.53 score for task 6 and 5 respectively.","PeriodicalId":378985,"journal":{"name":"Proceedings of the Sixth Social Media Mining for Health (#SMM4H) Workshop and Shared Task","volume":"58 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the Sixth Social Media Mining for Health (#SMM4H) Workshop and Shared Task","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.18653/V1/2021.SMM4H-1.33","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Social media platforms such as Twitter and Facebook have been utilised for various research studies, from the cohort-level discussion to community-driven approaches to address the challenges in utilizing social media data for health, clinical and biomedical information. Detection of medical jargon’s, named entity recognition, multi-word expression becomes the primary, fundamental steps in solving those challenges. In this paper, we enumerate the ULD-NUIG team’s system, designed as part of Social Media Mining for Health Applications (#SMM4H) Shared Task 2021. The team conducted a series of experiments to explore the challenges of task 6 and task 5. The submitted systems achieve F-1 0.84 and 0.53 score for task 6 and 5 respectively.