Identifying causal relations in tweets using deep learning: Use case on diabetes-related tweets from 2017-2021. (arXiv:2111.01225v4 [cs.CL] UPDATED)

Objective: Leveraging machine learning methods, we aim to extract both
explicit and implicit cause-effect associations in patient-reported,
diabetes-related tweets and provide a tool to better understand opinion,
feelings and observations shared within the diabetes online community from a
causality perspective. Materials and Methods: More than 30 million
diabetes-related tweets in English were collected between April 2017 and
January 2021. Deep learning and natural language processing methods were
applied to focus on tweets with personal and emotional content. A
cause-effect-tweet dataset …

arxiv deep learning diabetes learning relations