Ram Kadiyala


2024

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1024m at SMM4H 2024: Tasks 3, 5 & 6 - Self Reported Health Text Classification through Ensembles
Ram Kadiyala | M.v.p. Rao
Proceedings of The 9th Social Media Mining for Health Research and Applications (SMM4H 2024) Workshop and Shared Tasks

Social media is a great source of data for users reporting information and regarding their health and how various things have had an effect on them. This paper presents various approaches using Transformers and Large Language Models and their ensembles, their performance along with advantages and drawbacks for various tasks of SMM4H’24 - Classifying texts on impact of nature and outdoor spaces on the author’s mental health (Task 3), Binary classification of tweets reporting their children’s health disorders like Asthma, Autism, ADHD and Speech disorder (task 5), Binary classification of users self-reporting their age (task 6).
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