2024 ACL ACL 2024

DILAB at #SMM4H 2024: Analyzing Social Anxiety Effects through Context-Aware Transfer Learning on Reddit Data

Abstract

AbstractThis paper illustrates the system we design for Task 3 of the 9th Social Media Mining for Health (SMM4H 2024) shared tasks. The task presents posts made on the Reddit social media platform, specifically the *r/SocialAnxiety* subreddit, along with one or more outdoor activities as pre-determined keywords for each post. The task then requires each post to be categorized as either one of *positive*, *negative*, *no effect*, or *not outdoor activity* based on what effect the keyword(s) have on social anxiety. Our approach focuses on fine-tuning pre-trained language models to classify the posts. Additionally, we use fuzzy string matching to select only the text around the given keywords so that the model only has to focus on the contextual sentiment associated with the keywords. Using this system, our peak score is 0.65 macro-F1 on the validation set and 0.654 on test set.

🌉 Interdisciplinary Bridge — Artificial Intelligence and Data Science & Analytics and Deep Learning and Machine Learning and Natural Language Processing
🧭 Keyword Pioneer — social anxiety
🐝 Cross-Pollinator — Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Robotics, Security & Privacy, Speech & Audio