RevealED: Uncovering Pro-Eating Disorder Content on Twitter Using Deep Learning

TL;DR

This study develops a deep learning model, specifically a Vision Transformer, to identify pro-eating disorder content in Twitter images, revealing seasonal patterns and a rising trend over five years, influenced by stressors like COVID-19.

Contribution

Introduces a deep learning approach using Vision Transformers to detect pro-eating disorder content in social media images, highlighting temporal patterns and increasing prevalence.

Findings

Vision Transformer achieved 86.7% accuracy and 0.877 F1 score.

Pro-eating disorder content peaks in summer and correlates with stressors.

Content has been steadily rising over the past five years.

Abstract

The Covid-19 pandemic induced a vast increase in adolescents diagnosed with eating disorders and hospitalized due to eating disorders. This immense growth stemmed partially from the stress of the pandemic but also from increased exposure to content that promotes eating disorders via social media, which, within the last decade, has become plagued by pro-eating disorder content. This study aimed to create a deep learning model capable of determining whether a given social media post promotes eating disorders based solely on image data. Tweets from hashtags that have been documented to promote eating disorders along with Tweets from unrelated hashtags were collected. After prepossessing, these images were labeled as either pro-eating disorder or not based on which Twitter hashtag they were scraped from. Several deep-learning models were trained on the scraped dataset and were evaluated based on their accuracy, F1 score, precision, and recall. Ultimately, the Vision Transformer model was determined to be the most accurate, attaining an F1 score of 0.877 and an accuracy of 86.7% on the test set. The model, which was applied to unlabeled Twitter image data scraped from "#selfie", uncovered seasonal fluctuations in the relative abundance of pro-eating disorder content, which reached its peak in the summertime. These fluctuations correspond not only to the seasons, but also to stressors, such as the Covid-19 pandemic. Moreover, the Twitter image data indicated that the relative amount of pro-eating disorder content has been steadily rising over the last five years and is likely to continue increasing in the future.